def test_to_Sequence():
x = symbols('x')
R, Dx = DifferentialOperators(ZZ.old_poly_ring(x), 'Dx')
n = symbols('n', integer=True)
_, Sn = RecurrenceOperators(ZZ.old_poly_ring(n), 'Sn')
p = HolonomicFunction(x**2 * Dx**4 + x + Dx, x).to_sequence()
q = [(HolonomicSequence(1 + (n + 2) * Sn**2 +
(n**4 + 6 * n**3 + 11 * n**2 + 6 * n) * Sn**3), 0,
1)]
assert p == q
p = HolonomicFunction(x**2 * Dx**4 + x**3 + Dx**2, x).to_sequence()
q = [
(HolonomicSequence(1 + (n**4 + 14 * n**3 + 72 * n**2 + 163 * n + 140) *
Sn**5), 0, 0)
]
assert p == q
p = HolonomicFunction(x**3 * Dx**4 + 1 + Dx**2, x).to_sequence()
q = [(HolonomicSequence(1 + (n**4 - 2 * n**3 - n**2 + 2 * n) * Sn +
(n**2 + 3 * n + 2) * Sn**2), 0, 0)]
assert p == q
p = HolonomicFunction(3 * x**3 * Dx**4 + 2 * x * Dx + x * Dx**3,
x).to_sequence()
q = [(HolonomicSequence(2 * n +
(3 * n**4 - 6 * n**3 - 3 * n**2 + 6 * n) * Sn +
(n**3 + 3 * n**2 + 2 * n) * Sn**2), 0, 1)]
assert p == q
def hermite_normal_form(A, *, D=None, check_rank=False):
r"""
Compute the Hermite Normal Form of a Matrix *A* of integers.
Examples
========
>>> from sympy import Matrix
>>> from sympy.matrices.normalforms import hermite_normal_form
>>> m = Matrix([[12, 6, 4], [3, 9, 6], [2, 16, 14]])
>>> print(hermite_normal_form(m))
Matrix([[10, 0, 2], [0, 15, 3], [0, 0, 2]])
Parameters
==========
A : $m \times n$ ``Matrix`` of integers.
D : int, optional
Let $W$ be the HNF of *A*. If known in advance, a positive integer *D*
being any multiple of $\det(W)$ may be provided. In this case, if *A*
also has rank $m$, then we may use an alternative algorithm that works
mod *D* in order to prevent coefficient explosion.
check_rank : boolean, optional (default=False)
The basic assumption is that, if you pass a value for *D*, then
you already believe that *A* has rank $m$, so we do not waste time
checking it for you. If you do want this to be checked (and the
ordinary, non-modulo *D* algorithm to be used if the check fails), then
set *check_rank* to ``True``.
Returns
=======
``Matrix``
The HNF of matrix *A*.
Raises
======
DMDomainError
If the domain of the matrix is not :ref:`ZZ`.
DMShapeError
If the mod *D* algorithm is used but the matrix has more rows than
columns.
References
==========
.. [1] Cohen, H. *A Course in Computational Algebraic Number Theory.*
(See Algorithms 2.4.5 and 2.4.8.)
"""
# Accept any of Python int, SymPy Integer, and ZZ itself:
if D is not None and not ZZ.of_type(D):
D = ZZ(int(D))
return _hnf(A._rep, D=D, check_rank=check_rank).to_Matrix()
def test_QuotientRing():
I = QQ.old_poly_ring(x).ideal(x**2 + 1)
R = QQ.old_poly_ring(x) / I
assert R == QQ.old_poly_ring(x) / [x**2 + 1]
assert R == QQ.old_poly_ring(x) / QQ.old_poly_ring(x).ideal(x**2 + 1)
assert R != QQ.old_poly_ring(x)
assert R.convert(1) / x == -x + I
assert -1 + I == x**2 + I
assert R.convert(ZZ(1), ZZ) == 1 + I
assert R.convert(R.convert(x), R) == R.convert(x)
X = R.convert(x)
Y = QQ.old_poly_ring(x).convert(x)
assert -1 + I == X**2 + I
assert -1 + I == Y**2 + I
assert R.to_sympy(X) == x
raises(ValueError,
lambda: QQ.old_poly_ring(x) / QQ.old_poly_ring(x, y).ideal(x))
R = QQ.old_poly_ring(x, order="ilex")
I = R.ideal(x)
assert R.convert(1) + I == (R / I).convert(1)
def denom(self, a):
"""Get the denominator of ``a``."""
ZZ = self.dom.get_ring()
QQ = self.dom
ZZ_I = self.get_ring()
denom_ZZ = ZZ.lcm(QQ.denom(a.x), QQ.denom(a.y))
return ZZ_I(denom_ZZ, ZZ.zero)
def test_to_expr():
x = symbols('x')
R, Dx = DifferentialOperators(ZZ.old_poly_ring(x), 'Dx')
p = HolonomicFunction(Dx - 1, x, 0, [1]).to_expr()
q = exp(x)
assert p == q
p = HolonomicFunction(Dx**2 + 1, x, 0, [1, 0]).to_expr()
q = cos(x)
assert p == q
p = HolonomicFunction(Dx**2 - 1, x, 0, [1, 0]).to_expr()
q = cosh(x)
assert p == q
p = HolonomicFunction(2 + (4*x - 1)*Dx + \
(x**2 - x)*Dx**2, x, 0, [1, 2]).to_expr().expand()
q = 1 / (x**2 - 2 * x + 1)
assert p == q
p = expr_to_holonomic(sin(x)**2 / x).integrate((x, 0, x)).to_expr()
q = (sin(x)**2 / x).integrate((x, 0, x))
assert p == q
C_0, C_1, C_2, C_3 = symbols('C_0, C_1, C_2, C_3')
p = expr_to_holonomic(log(1 + x**2)).to_expr()
q = C_2 * log(x**2 + 1)
assert p == q
p = expr_to_holonomic(log(1 + x**2)).diff().to_expr()
q = C_0 * x / (x**2 + 1)
assert p == q
p = expr_to_holonomic(erf(x) + x).to_expr()
q = 3 * C_3 * x - 3 * sqrt(pi) * C_3 * erf(x) / 2 + x + 2 * x / sqrt(pi)
assert p == q
p = expr_to_holonomic(sqrt(x), x0=1).to_expr()
assert p == sqrt(x)
assert expr_to_holonomic(sqrt(x)).to_expr() == sqrt(x)
p = expr_to_holonomic(sqrt(1 + x**2)).to_expr()
assert p == sqrt(1 + x**2)
p = expr_to_holonomic((2 * x**2 + 1)**Rational(2, 3)).to_expr()
assert p == (2 * x**2 + 1)**Rational(2, 3)
p = expr_to_holonomic(sqrt(-x**2 + 2 * x)).to_expr()
assert p == sqrt(x) * sqrt(-x + 2)
p = expr_to_holonomic((-2 * x**3 + 7 * x)**Rational(2, 3)).to_expr()
q = x**Rational(2, 3) * (-2 * x**2 + 7)**Rational(2, 3)
assert p == q
p = from_hyper(hyper((-2, -3), (S.Half, ), x))
s = hyperexpand(hyper((-2, -3), (S.Half, ), x))
D_0 = Symbol('D_0')
C_0 = Symbol('C_0')
assert (p.to_expr().subs({C_0: 1, D_0: 0}) - s).simplify() == 0
p.y0 = {0: [1], S.Half: [0]}
assert p.to_expr() == s
assert expr_to_holonomic(x**5).to_expr() == x**5
assert expr_to_holonomic(2*x**3-3*x**2).to_expr().expand() == \
2*x**3-3*x**2
a = symbols("a")
p = (expr_to_holonomic(1.4 * x) * expr_to_holonomic(a * x, x)).to_expr()
q = 1.4 * a * x**2
assert p == q
p = (expr_to_holonomic(1.4 * x) + expr_to_holonomic(a * x, x)).to_expr()
q = x * (a + 1.4)
assert p == q
p = (expr_to_holonomic(1.4 * x) + expr_to_holonomic(x)).to_expr()
assert p == 2.4 * x
def test_HolonomicFunction_addition():
x = symbols('x')
R, Dx = DifferentialOperators(ZZ.old_poly_ring(x), 'Dx')
p = HolonomicFunction(Dx**2 * x, x)
q = HolonomicFunction((2) * Dx + (x) * Dx**2, x)
assert p == q
p = HolonomicFunction(x * Dx + 1, x)
q = HolonomicFunction(Dx + 1, x)
r = HolonomicFunction((x - 2) + (x**2 - 2) * Dx + (x**2 - x) * Dx**2, x)
assert p + q == r
p = HolonomicFunction(x * Dx + Dx**2 * (x**2 + 2), x)
q = HolonomicFunction(Dx - 3, x)
r = HolonomicFunction((-54 * x**2 - 126 * x - 150) + (-135 * x**3 - 252 * x**2 - 270 * x + 140) * Dx +\
(-27 * x**4 - 24 * x**2 + 14 * x - 150) * Dx**2 + \
(9 * x**4 + 15 * x**3 + 38 * x**2 + 30 * x +40) * Dx**3, x)
assert p + q == r
p = HolonomicFunction(Dx**5 - 1, x)
q = HolonomicFunction(x**3 + Dx, x)
r = HolonomicFunction((-x**18 + 45*x**14 - 525*x**10 + 1575*x**6 - x**3 - 630*x**2) + \
(-x**15 + 30*x**11 - 195*x**7 + 210*x**3 - 1)*Dx + (x**18 - 45*x**14 + 525*x**10 - \
1575*x**6 + x**3 + 630*x**2)*Dx**5 + (x**15 - 30*x**11 + 195*x**7 - 210*x**3 + \
1)*Dx**6, x)
assert p + q == r
p = x**2 + 3 * x + 8
q = x**3 - 7 * x + 5
p = p * Dx - p.diff()
q = q * Dx - q.diff()
r = HolonomicFunction(p, x) + HolonomicFunction(q, x)
s = HolonomicFunction((6*x**2 + 18*x + 14) + (-4*x**3 - 18*x**2 - 62*x + 10)*Dx +\
(x**4 + 6*x**3 + 31*x**2 - 10*x - 71)*Dx**2, x)
assert r == s
def test_pickling_polys_polyclasses():
from sympy.polys.polyclasses import DMP, DMF, ANP
for c in (DMP, DMP([[ZZ(1)], [ZZ(2)], [ZZ(3)]], ZZ)):
check(c)
for c in (DMF, DMF(([ZZ(1), ZZ(2)], [ZZ(1), ZZ(3)]), ZZ)):
check(c)
for c in (ANP, ANP([QQ(1), QQ(2)], [QQ(1), QQ(2), QQ(3)], QQ)):
check(c)
def test_integrate():
x = symbols('x')
R, Dx = DifferentialOperators(ZZ.old_poly_ring(x), 'Dx')
p = expr_to_holonomic(sin(x)**2 / x, x0=1).integrate((x, 2, 3))
q = '0.166270406994788'
assert sstr(p) == q
p = expr_to_holonomic(sin(x)).integrate((x, 0, x)).to_expr()
q = 1 - cos(x)
assert p == q
p = expr_to_holonomic(sin(x)).integrate((x, 0, 3))
q = 1 - cos(3)
assert p == q
p = expr_to_holonomic(sin(x) / x, x0=1).integrate((x, 1, 2))
q = '0.659329913368450'
assert sstr(p) == q
p = expr_to_holonomic(sin(x)**2 / x, x0=1).integrate((x, 1, 0))
q = '-0.423690480850035'
assert sstr(p) == q
p = expr_to_holonomic(sin(x) / x)
assert p.integrate(x).to_expr() == Si(x)
assert p.integrate((x, 0, 2)) == Si(2)
p = expr_to_holonomic(sin(x)**2 / x)
q = p.to_expr()
assert p.integrate(x).to_expr() == q.integrate((x, 0, x))
assert p.integrate((x, 0, 1)) == q.integrate((x, 0, 1))
assert expr_to_holonomic(1 / x, x0=1).integrate(x).to_expr() == log(x)
p = expr_to_holonomic((x + 1)**3 * exp(-x), x0=-1).integrate(x).to_expr()
q = (-x**3 - 6 * x**2 - 15 * x + 6 * exp(x + 1) - 16) * exp(-x)
assert p == q
p = expr_to_holonomic(cos(x)**2 / x**2, y0={
-2: [1, 0, -1]
}).integrate(x).to_expr()
q = -Si(2 * x) - cos(x)**2 / x
assert p == q
p = expr_to_holonomic(sqrt(x**2 + x)).integrate(x).to_expr()
q = (x**Rational(3, 2) * (2 * x**2 + 3 * x + 1) -
x * sqrt(x + 1) * asinh(sqrt(x))) / (4 * x * sqrt(x + 1))
assert p == q
p = expr_to_holonomic(sqrt(x**2 + 1)).integrate(x).to_expr()
q = (sqrt(x**2 + 1)).integrate(x)
assert (p - q).simplify() == 0
p = expr_to_holonomic(1 / x**2, y0={-2: [1, 0, 0]})
r = expr_to_holonomic(1 / x**2, lenics=3)
assert p == r
q = expr_to_holonomic(cos(x)**2)
assert (r * q).integrate(x).to_expr() == -Si(2 * x) - cos(x)**2 / x
def is_int(c):
r"""
Test whether an argument is of an acceptable type to be used as an integer.
Explanation
===========
Returns ``True`` on any argument of type ``int`` or :ref:`ZZ`.
See Also
========
is_rat
"""
# If gmpy2 is installed then ``ZZ.of_type()`` accepts only
# ``mpz``, not ``int``, so we need another clause to ensure ``int`` is
# accepted.
return isinstance(c, int) or ZZ.of_type(c)
def test_series():
x = symbols('x')
R, Dx = DifferentialOperators(ZZ.old_poly_ring(x), 'Dx')
p = HolonomicFunction(Dx**2 + 2 * x * Dx, x, 0, [0, 1]).series(n=10)
q = x - x**3 / 3 + x**5 / 10 - x**7 / 42 + x**9 / 216 + O(x**10)
assert p == q
p = HolonomicFunction(Dx - 1, x).composition(x**2, 0, [1]) # e^(x**2)
q = HolonomicFunction(Dx**2 + 1, x, 0, [1, 0]) # cos(x)
r = (p * q).series(n=10) # expansion of cos(x) * exp(x**2)
s = 1 + x**2 / 2 + x**4 / 24 - 31 * x**6 / 720 - 179 * x**8 / 8064 + O(x**
10)
assert r == s
t = HolonomicFunction((1 + x) * Dx**2 + Dx, x, 0, [0, 1]) # log(1 + x)
r = (p * t + q).series(n=10)
s = 1 + x - x**2 + 4*x**3/3 - 17*x**4/24 + 31*x**5/30 - 481*x**6/720 +\
71*x**7/105 - 20159*x**8/40320 + 379*x**9/840 + O(x**10)
assert r == s
p = HolonomicFunction((6+6*x-3*x**2) - (10*x-3*x**2-3*x**3)*Dx + \
(4-6*x**3+2*x**4)*Dx**2, x, 0, [0, 1]).series(n=7)
q = x + x**3 / 6 - 3 * x**4 / 16 + x**5 / 20 - 23 * x**6 / 960 + O(x**7)
assert p == q
p = HolonomicFunction((6+6*x-3*x**2) - (10*x-3*x**2-3*x**3)*Dx + \
(4-6*x**3+2*x**4)*Dx**2, x, 0, [1, 0]).series(n=7)
q = 1 - 3 * x**2 / 4 - x**3 / 4 - 5 * x**4 / 32 - 3 * x**5 / 40 - 17 * x**6 / 384 + O(
x**7)
assert p == q
p = expr_to_holonomic(erf(x) + x).series(n=10)
C_3 = symbols('C_3')
q = (erf(x) + x).series(n=10)
assert p.subs(C_3, -2 / (3 * sqrt(pi))) == q
assert expr_to_holonomic(
sqrt(x**3 + x)).series(n=10) == sqrt(x**3 + x).series(n=10)
assert expr_to_holonomic((2 * x - 3 * x**2)**Rational(
1, 3)).series() == ((2 * x - 3 * x**2)**Rational(1, 3)).series()
assert expr_to_holonomic(sqrt(x**2 - x)).series() == (sqrt(x**2 -
x)).series()
assert expr_to_holonomic(cos(x)**2 / x**2, y0={
-2: [1, 0, -1]
}).series(n=10) == (cos(x)**2 / x**2).series(n=10)
assert expr_to_holonomic(cos(x)**2 / x**2, x0=1).series(
n=10).together() == (cos(x)**2 / x**2).series(n=10, x0=1).together()
assert expr_to_holonomic(cos(x-1)**2/(x-1)**2, x0=1, y0={-2: [1, 0, -1]}).series(n=10) \
== (cos(x-1)**2/(x-1)**2).series(x0=1, n=10)
def test_diff():
x, y = symbols('x, y')
R, Dx = DifferentialOperators(ZZ.old_poly_ring(x), 'Dx')
p = HolonomicFunction(x * Dx**2 + 1, x, 0, [0, 1])
assert p.diff().to_expr() == p.to_expr().diff().simplify()
p = HolonomicFunction(Dx**2 - 1, x, 0, [1, 0])
assert p.diff(x, 2).to_expr() == p.to_expr()
p = expr_to_holonomic(Si(x))
assert p.diff().to_expr() == sin(x) / x
assert p.diff(y) == 0
C_0, C_1, C_2, C_3 = symbols('C_0, C_1, C_2, C_3')
q = Si(x)
assert p.diff(x).to_expr() == q.diff()
assert p.diff(x, 2).to_expr().subs(C_0, Rational(-1,
3)).cancel() == q.diff(
x, 2).cancel()
assert p.diff(x, 3).series().subs({
C_3: Rational(-1, 3),
C_0: 0
}) == q.diff(x, 3).series()
def test_polymatrix_constructor():
M1 = PolyMatrix([[x, y]], ring=QQ[x,y])
assert M1.ring == QQ[x,y]
assert M1.domain == QQ
assert M1.gens == (x, y)
assert M1.shape == (1, 2)
assert M1.rows == 1
assert M1.cols == 2
assert len(M1) == 2
assert list(M1) == [Poly(x, (x, y), domain=QQ), Poly(y, (x, y), domain=QQ)]
M2 = PolyMatrix([[x, y]], ring=QQ[x][y])
assert M2.ring == QQ[x][y]
assert M2.domain == QQ[x]
assert M2.gens == (y,)
assert M2.shape == (1, 2)
assert M2.rows == 1
assert M2.cols == 2
assert len(M2) == 2
assert list(M2) == [Poly(x, (y,), domain=QQ[x]), Poly(y, (y,), domain=QQ[x])]
assert PolyMatrix([[x, y]], y) == PolyMatrix([[x, y]], ring=ZZ.frac_field(x)[y])
assert PolyMatrix([[x, y]], ring='ZZ[x,y]') == PolyMatrix([[x, y]], ring=ZZ[x,y])
assert PolyMatrix([[x, y]], (x, y)) == PolyMatrix([[x, y]], ring=QQ[x,y])
assert PolyMatrix([[x, y]], x, y) == PolyMatrix([[x, y]], ring=QQ[x,y])
assert PolyMatrix([x, y]) == PolyMatrix([[x], [y]], ring=QQ[x,y])
assert PolyMatrix(1, 2, [x, y]) == PolyMatrix([[x, y]], ring=QQ[x,y])
assert PolyMatrix(1, 2, lambda i,j: [x,y][j]) == PolyMatrix([[x, y]], ring=QQ[x,y])
assert PolyMatrix(0, 2, [], x, y).shape == (0, 2)
assert PolyMatrix(2, 0, [], x, y).shape == (2, 0)
assert PolyMatrix([[], []], x, y).shape == (2, 0)
assert PolyMatrix(ring=QQ[x,y]) == PolyMatrix(0, 0, [], ring=QQ[x,y]) == PolyMatrix([], ring=QQ[x,y])
raises(TypeError, lambda: PolyMatrix())
raises(TypeError, lambda: PolyMatrix(1))
assert PolyMatrix([Poly(x), Poly(y)]) == PolyMatrix([[x], [y]], ring=ZZ[x,y])
# XXX: Maybe a bug in parallel_poly_from_expr (x lost from gens and domain):
assert PolyMatrix([Poly(y, x), 1]) == PolyMatrix([[y], [1]], ring=QQ[y])
def is_rat(c):
r"""
Test whether an argument is of an acceptable type to be used as a rational
number.
Explanation
===========
Returns ``True`` on any argument of type ``int``, :ref:`ZZ`, or :ref:`QQ`.
See Also
========
is_int
"""
# ``c in QQ`` is too accepting (e.g. ``3.14 in QQ`` is ``True``),
# ``QQ.of_type(c)`` is too demanding (e.g. ``QQ.of_type(3)`` is ``False``).
#
# Meanwhile, if gmpy2 is installed then ``ZZ.of_type()`` accepts only
# ``mpz``, not ``int``, so we need another clause to ensure ``int`` is
# accepted.
return isinstance(c, int) or ZZ.of_type(c) or QQ.of_type(c)
def test_HolonomicFunction_multiplication():
x = symbols('x')
R, Dx = DifferentialOperators(ZZ.old_poly_ring(x), 'Dx')
p = HolonomicFunction(Dx + x + x * Dx**2, x)
q = HolonomicFunction(x * Dx + Dx * x + Dx**2, x)
r = HolonomicFunction((8*x**6 + 4*x**4 + 6*x**2 + 3) + (24*x**5 - 4*x**3 + 24*x)*Dx + \
(8*x**6 + 20*x**4 + 12*x**2 + 2)*Dx**2 + (8*x**5 + 4*x**3 + 4*x)*Dx**3 + \
(2*x**4 + x**2)*Dx**4, x)
assert p * q == r
p = HolonomicFunction(Dx**2 + 1, x)
q = HolonomicFunction(Dx - 1, x)
r = HolonomicFunction((2) + (-2) * Dx + (1) * Dx**2, x)
assert p * q == r
p = HolonomicFunction(Dx**2 + 1 + x + Dx, x)
q = HolonomicFunction((Dx * x - 1)**2, x)
r = HolonomicFunction((4*x**7 + 11*x**6 + 16*x**5 + 4*x**4 - 6*x**3 - 7*x**2 - 8*x - 2) + \
(8*x**6 + 26*x**5 + 24*x**4 - 3*x**3 - 11*x**2 - 6*x - 2)*Dx + \
(8*x**6 + 18*x**5 + 15*x**4 - 3*x**3 - 6*x**2 - 6*x - 2)*Dx**2 + (8*x**5 + \
10*x**4 + 6*x**3 - 2*x**2 - 4*x)*Dx**3 + (4*x**5 + 3*x**4 - x**2)*Dx**4, x)
assert p * q == r
p = HolonomicFunction(x * Dx**2 - 1, x)
q = HolonomicFunction(Dx * x - x, x)
r = HolonomicFunction((x - 3) + (-2 * x + 2) * Dx + (x) * Dx**2, x)
assert p * q == r
def test_HolonomicFunction_composition():
x = symbols('x')
R, Dx = DifferentialOperators(ZZ.old_poly_ring(x), 'Dx')
p = HolonomicFunction(Dx - 1, x).composition(x**2 + x)
r = HolonomicFunction((-2 * x - 1) + Dx, x)
assert p == r
p = HolonomicFunction(Dx**2 + 1, x).composition(x**5 + x**2 + 1)
r = HolonomicFunction((125*x**12 + 150*x**9 + 60*x**6 + 8*x**3) + (-20*x**3 - 2)*Dx + \
(5*x**4 + 2*x)*Dx**2, x)
assert p == r
p = HolonomicFunction(Dx**2 * x + x, x).composition(2 * x**3 + x**2 + 1)
r = HolonomicFunction((216*x**9 + 324*x**8 + 180*x**7 + 152*x**6 + 112*x**5 + \
36*x**4 + 4*x**3) + (24*x**4 + 16*x**3 + 3*x**2 - 6*x - 1)*Dx + (6*x**5 + 5*x**4 + \
x**3 + 3*x**2 + x)*Dx**2, x)
assert p == r
p = HolonomicFunction(Dx**2 + 1, x).composition(1 - x**2)
r = HolonomicFunction((4 * x**3) - Dx + x * Dx**2, x)
assert p == r
p = HolonomicFunction(Dx**2 + 1, x).composition(x - 2 / (x**2 + 1))
r = HolonomicFunction((x**12 + 6*x**10 + 12*x**9 + 15*x**8 + 48*x**7 + 68*x**6 + \
72*x**5 + 111*x**4 + 112*x**3 + 54*x**2 + 12*x + 1) + (12*x**8 + 32*x**6 + \
24*x**4 - 4)*Dx + (x**12 + 6*x**10 + 4*x**9 + 15*x**8 + 16*x**7 + 20*x**6 + 24*x**5+ \
15*x**4 + 16*x**3 + 6*x**2 + 4*x + 1)*Dx**2, x)
assert p == r
class GaussianIntegerRing(GaussianDomain, Ring):
r"""Ring of Gaussian integers ``ZZ_I``
The :ref:`ZZ_I` domain represents the `Gaussian integers`_ `\mathbb{Z}[i]`
as a :py:class:`~.Domain` in the domain system (see
:ref:`polys-domainsintro`).
By default a :py:class:`~.Poly` created from an expression with
coefficients that are combinations of integers and ``I`` (`\sqrt{-1}`)
will have the domain :ref:`ZZ_I`.
>>> from sympy import Poly, Symbol, I
>>> x = Symbol('x')
>>> p = Poly(x**2 + I)
>>> p
Poly(x**2 + I, x, domain='ZZ_I')
>>> p.domain
ZZ_I
The :ref:`ZZ_I` domain can be used to factorise polynomials that are
reducible over the Gaussian integers.
>>> from sympy import factor
>>> factor(x**2 + 1)
x**2 + 1
>>> factor(x**2 + 1, domain='ZZ_I')
(x - I)*(x + I)
The corresponding `field of fractions`_ is the domain of the Gaussian
rationals :ref:`QQ_I`. Conversely :ref:`ZZ_I` is the `ring of integers`_
of :ref:`QQ_I`.
>>> from sympy import ZZ_I, QQ_I
>>> ZZ_I.get_field()
QQ_I
>>> QQ_I.get_ring()
ZZ_I
When using the domain directly :ref:`ZZ_I` can be used as a constructor.
>>> ZZ_I(3, 4)
(3 + 4*I)
>>> ZZ_I(5)
(5 + 0*I)
The domain elements of :ref:`ZZ_I` are instances of
:py:class:`~.GaussianInteger` which support the rings operations
``+,-,*,**``.
>>> z1 = ZZ_I(5, 1)
>>> z2 = ZZ_I(2, 3)
>>> z1
(5 + 1*I)
>>> z2
(2 + 3*I)
>>> z1 + z2
(7 + 4*I)
>>> z1 * z2
(7 + 17*I)
>>> z1 ** 2
(24 + 10*I)
Both floor (``//``) and modulo (``%``) division work with
:py:class:`~.GaussianInteger` (see the :py:meth:`~.Domain.div` method).
>>> z3, z4 = ZZ_I(5), ZZ_I(1, 3)
>>> z3 // z4 # floor division
(1 + -1*I)
>>> z3 % z4 # modulo division (remainder)
(1 + -2*I)
>>> (z3//z4)*z4 + z3%z4 == z3
True
True division (``/``) in :ref:`ZZ_I` gives an element of :ref:`QQ_I`. The
:py:meth:`~.Domain.exquo` method can be used to divide in :ref:`ZZ_I` when
exact division is possible.
>>> z1 / z2
(1 + -1*I)
>>> ZZ_I.exquo(z1, z2)
(1 + -1*I)
>>> z3 / z4
(1/2 + -3/2*I)
>>> ZZ_I.exquo(z3, z4)
Traceback (most recent call last):
...
ExactQuotientFailed: (1 + 3*I) does not divide (5 + 0*I) in ZZ_I
The :py:meth:`~.Domain.gcd` method can be used to compute the `gcd`_ of any
two elements.
>>> ZZ_I.gcd(ZZ_I(10), ZZ_I(2))
(2 + 0*I)
>>> ZZ_I.gcd(ZZ_I(5), ZZ_I(2, 1))
(2 + 1*I)
.. _Gaussian integers: https://en.wikipedia.org/wiki/Gaussian_integer
.. _gcd: https://en.wikipedia.org/wiki/Greatest_common_divisor
"""
dom = ZZ
dtype = GaussianInteger
zero = dtype(ZZ(0), ZZ(0))
one = dtype(ZZ(1), ZZ(0))
imag_unit = dtype(ZZ(0), ZZ(1))
units = (one, imag_unit, -one, -imag_unit) # powers of i
rep = 'ZZ_I'
is_GaussianRing = True
is_ZZ_I = True
def __init__(self): # override Domain.__init__
"""For constructing ZZ_I."""
def get_ring(self):
"""Returns a ring associated with ``self``. """
return self
def get_field(self):
"""Returns a field associated with ``self``. """
return QQ_I
def normalize(self, d, *args):
"""Return first quadrant element associated with ``d``.
Also multiply the other arguments by the same power of i.
"""
unit = self.canonical_unit(d)
d *= unit
args = tuple(a * unit for a in args)
return (d, ) + args if args else d
def gcd(self, a, b):
"""Greatest common divisor of a and b over ZZ_I."""
while b:
a, b = b, a % b
return self.normalize(a)
def lcm(self, a, b):
"""Least common multiple of a and b over ZZ_I."""
return (a * b) // self.gcd(a, b)
def from_GaussianIntegerRing(K1, a, K0):
"""Convert a ZZ_I element to ZZ_I."""
return a
def from_GaussianRationalField(K1, a, K0):
"""Convert a QQ_I element to ZZ_I."""
return K1.new(ZZ.convert(a.x), ZZ.convert(a.y))
def test_trace():
a = [[ZZ(3), ZZ(7), ZZ(4)], [ZZ(2), ZZ(4), ZZ(5)], [ZZ(6), ZZ(2), ZZ(3)]]
b = eye(2, ZZ)
assert trace(a, ZZ) == ZZ(10)
assert trace(b, ZZ) == ZZ(2)
def test_mulmatscaler():
a = eye(3, ZZ)
b = [[ZZ(3), ZZ(7), ZZ(4)], [ZZ(2), ZZ(4), ZZ(5)], [ZZ(6), ZZ(2), ZZ(3)]]
assert mulmatscaler(a, ZZ(4), ZZ) == [[ZZ(4), ZZ(0), ZZ(0)],
[ZZ(0), ZZ(4), ZZ(0)],
[ZZ(0), ZZ(0), ZZ(4)]]
assert mulmatscaler(b, ZZ(1), ZZ) == [[ZZ(3), ZZ(7), ZZ(4)],
[ZZ(2), ZZ(4), ZZ(5)],
[ZZ(6), ZZ(2), ZZ(3)]]
def from_GaussianRationalField(K1, a, K0):
"""Convert a QQ_I element to ZZ_I."""
return K1.new(ZZ.convert(a.x), ZZ.convert(a.y))
def test_mulmatmat():
a = [[ZZ(3), ZZ(4)], [ZZ(5), ZZ(6)]]
b = [[ZZ(1), ZZ(2)], [ZZ(7), ZZ(8)]]
c = eye(2, ZZ)
d = [[ZZ(6)], [ZZ(7)]]
assert mulmatmat(a, b, ZZ) == [[ZZ(31), ZZ(38)], [ZZ(47), ZZ(58)]]
assert mulmatmat(a, c, ZZ) == [[ZZ(3), ZZ(4)], [ZZ(5), ZZ(6)]]
assert mulmatmat(b, d, ZZ) == [[ZZ(20)], [ZZ(98)]]
def test_sub():
a = [[ZZ(3), ZZ(7), ZZ(4)], [ZZ(2), ZZ(4), ZZ(5)], [ZZ(6), ZZ(2), ZZ(3)]]
b = [[ZZ(5), ZZ(4), ZZ(9)], [ZZ(3), ZZ(7), ZZ(1)],
[ZZ(12), ZZ(13), ZZ(14)]]
c = [[ZZ(12)], [ZZ(17)], [ZZ(21)]]
d = [[ZZ(3)], [ZZ(4)], [ZZ(5)]]
e = [[ZZ(12), ZZ(78)], [ZZ(56), ZZ(79)]]
f = [[ZZ.zero, ZZ.zero], [ZZ.zero, ZZ.zero]]
assert sub(a, b, ZZ) == [[ZZ(-2), ZZ(3), ZZ(-5)], [ZZ(-1),
ZZ(-3),
ZZ(4)],
[ZZ(-6), ZZ(-11), ZZ(-11)]]
assert sub(c, d, ZZ) == [[ZZ(9)], [ZZ(13)], [ZZ(16)]]
assert sub(e, f, ZZ) == e
def test_add():
a = [[ZZ(3), ZZ(7), ZZ(4)], [ZZ(2), ZZ(4), ZZ(5)], [ZZ(6), ZZ(2), ZZ(3)]]
b = [[ZZ(5), ZZ(4), ZZ(9)], [ZZ(3), ZZ(7), ZZ(1)],
[ZZ(12), ZZ(13), ZZ(14)]]
c = [[ZZ(12)], [ZZ(17)], [ZZ(21)]]
d = [[ZZ(3)], [ZZ(4)], [ZZ(5)]]
e = [[ZZ(12), ZZ(78)], [ZZ(56), ZZ(79)]]
f = [[ZZ.zero, ZZ.zero], [ZZ.zero, ZZ.zero]]
assert add(a, b, ZZ) == [[ZZ(8), ZZ(11), ZZ(13)], [ZZ(5),
ZZ(11),
ZZ(6)],
[ZZ(18), ZZ(15), ZZ(17)]]
assert add(c, d, ZZ) == [[ZZ(15)], [ZZ(21)], [ZZ(26)]]
assert add(e, f, ZZ) == e
def round_two(T, radicals=None):
r"""
Zassenhaus's "Round 2" algorithm.
Explanation
===========
Carry out Zassenhaus's "Round 2" algorithm on a monic irreducible
polynomial *T* over :ref:`ZZ`. This computes an integral basis and the
discriminant for the field $K = \mathbb{Q}[x]/(T(x))$.
Ordinarily this function need not be called directly, as one can instead
access the :py:meth:`~.AlgebraicField.maximal_order`,
:py:meth:`~.AlgebraicField.integral_basis`, and
:py:meth:`~.AlgebraicField.discriminant` methods of an
:py:class:`~.AlgebraicField`.
Examples
========
Working through an AlgebraicField:
>>> from sympy import Poly, QQ
>>> from sympy.abc import x
>>> T = Poly(x ** 3 + x ** 2 - 2 * x + 8)
>>> K = QQ.alg_field_from_poly(T, "theta")
>>> print(K.maximal_order())
Submodule[[2, 0, 0], [0, 2, 0], [0, 1, 1]]/2
>>> print(K.discriminant())
-503
>>> print(K.integral_basis(fmt='sympy'))
[1, theta, theta/2 + theta**2/2]
Calling directly:
>>> from sympy import Poly
>>> from sympy.abc import x
>>> from sympy.polys.numberfields.basis import round_two
>>> T = Poly(x ** 3 + x ** 2 - 2 * x + 8)
>>> print(round_two(T))
(Submodule[[2, 0, 0], [0, 2, 0], [0, 1, 1]]/2, -503)
The nilradicals mod $p$ that are sometimes computed during the Round Two
algorithm may be useful in further calculations. Pass a dictionary under
`radicals` to receive these:
>>> T = Poly(x**3 + 3*x**2 + 5)
>>> rad = {}
>>> ZK, dK = round_two(T, radicals=rad)
>>> print(rad)
{3: Submodule[[-1, 1, 0], [-1, 0, 1]]}
Parameters
==========
T : :py:class:`~.Poly`
The irreducible monic polynomial over :ref:`ZZ` defining the number
field.
radicals : dict, optional
This is a way for any $p$-radicals (if computed) to be returned by
reference. If desired, pass an empty dictionary. If the algorithm
reaches the point where it computes the nilradical mod $p$ of the ring
of integers $Z_K$, then an $\mathbb{F}_p$-basis for this ideal will be
stored in this dictionary under the key ``p``. This can be useful for
other algorithms, such as prime decomposition.
Returns
=======
Pair ``(ZK, dK)``, where:
``ZK`` is a :py:class:`~sympy.polys.numberfields.modules.Submodule`
representing the maximal order.
``dK`` is the discriminant of the field $K = \mathbb{Q}[x]/(T(x))$.
See Also
========
.AlgebraicField.maximal_order
.AlgebraicField.integral_basis
.AlgebraicField.discriminant
References
==========
.. [1] Cohen, H. *A Course in Computational Algebraic Number Theory.*
"""
if T.domain == QQ:
try:
T = Poly(T, domain=ZZ)
except CoercionFailed:
pass # Let the error be raised by the next clause.
if (not T.is_univariate or not T.is_irreducible or not T.is_monic
or not T.domain == ZZ):
raise ValueError(
'Round 2 requires a monic irreducible univariate polynomial over ZZ.'
)
n = T.degree()
D = T.discriminant()
D_modulus = ZZ.from_sympy(abs(D))
# D must be 0 or 1 mod 4 (see Cohen Sec 4.4), which ensures we can write
# it in the form D = D_0 * F**2, where D_0 is 1 or a fundamental discriminant.
_, F = extract_fundamental_discriminant(D)
Ztheta = PowerBasis(T)
H = Ztheta.whole_submodule()
nilrad = None
while F:
# Next prime:
p, e = F.popitem()
U_bar, m = _apply_Dedekind_criterion(T, p)
if m == 0:
continue
# For a given prime p, the first enlargement of the order spanned by
# the current basis can be done in a simple way:
U = Ztheta.element_from_poly(Poly(U_bar, domain=ZZ))
# TODO:
# Theory says only first m columns of the U//p*H term below are needed.
# Could be slightly more efficient to use only those. Maybe `Submodule`
# class should support a slice operator?
H = H.add(U // p * H, hnf_modulus=D_modulus)
if e <= m:
continue
# A second, and possibly more, enlargements for p will be needed.
# These enlargements require a more involved procedure.
q = p
while q < n:
q *= p
H1, nilrad = _second_enlargement(H, p, q)
while H1 != H:
H = H1
H1, nilrad = _second_enlargement(H, p, q)
# Note: We do not store all nilradicals mod p, only the very last. This is
# because, unless computed against the entire integral basis, it might not
# be accurate. (In other words, if H was not already equal to ZK when we
# passed it to `_second_enlargement`, then we can't trust the nilradical
# so computed.) Example: if T(x) = x ** 3 + 15 * x ** 2 - 9 * x + 13, then
# F is divisible by 2, 3, and 7, and the nilradical mod 2 as computed above
# will not be accurate for the full, maximal order ZK.
if nilrad is not None and isinstance(radicals, dict):
radicals[p] = nilrad
ZK = H
# Pre-set expensive boolean properties which we already know to be true:
ZK._starts_with_unity = True
ZK._is_sq_maxrank_HNF = True
dK = (D * ZK.matrix.det()**2) // ZK.denom**(2 * n)
return ZK, dK
def test_transpose():
a = [[ZZ(3), ZZ(7), ZZ(4)], [ZZ(2), ZZ(4), ZZ(5)], [ZZ(6), ZZ(2), ZZ(3)]]
b = eye(4, ZZ)
assert transpose(a, ZZ) == ([[ZZ(3), ZZ(2), ZZ(6)], [ZZ(7), ZZ(4), ZZ(2)], [ZZ(4), ZZ(5), ZZ(3)]])
assert transpose(b, ZZ) == b