def poly_factor(poly):
P = poly.copy()
out = []
# Divide out the content
if P.content != 1:
out.append(QPoly([P.content]))
P = P.primitive_part
# Use rational roots to find linear factors
# A root may have multiplicity so we check each root until it doesn't
# divide anymore
lin = rational_roots(poly)
for f in lin:
while True:
d, m = divmod(P, QPoly([-f.n, f.d]))
if m == QPoly([0]):
out.append(QPoly([-f.n, f.d]))
P = P // out[-1]
else:
break
# Then do some Kronecker factorization on what's left
out += kronecker_factorization(P)
out.sort(key=len, reverse=True)
return out
def cast_to_poly(self, N):
"""Truncates the power series and returns a polynomial"""
P = QPoly([0])
x = QPoly([0, 1])
for pos, val in enumerate(self.a):
if pos > N:
break
P += val * (x - self.c)**pos
return P
def complete_the_square(poly):
"""Returns a tuple (x,y,z) such that x(y)^2+z is equal to poly"""
assert type(poly) == QPoly
assert len(poly) == 3, "Must be a quadratic"
assert poly[1] % 2 == Rational(0), "Linear coefficient must be even"
a = poly[2]
h = poly[1] // (2 * a)
k = poly[0] - a * (h * h)
hq = QPoly([poly[1] // (2 * a), 1])
return QPolySum([QPolyProd([QPoly([a]), hq, hq]),
QPoly([k])]) # a, QPoly( [h,1] ), k
def lagrange_interpolation(X, Y):
"""Lagrange Polynomial"""
final = QPoly([0])
for x, y in zip(X, Y):
out = QPoly([y])
for m in X:
if m != x:
d = Rational(1, (x - m))
print(d)
P = QPoly([-m, 1])
print(P)
print(P * d)
print(out)
print(out * P * d)
print()
out *= P * d
final += out
return final
def rfunc_asymptotes(rfunc):
"""Approximate asymptotes of a rational function"""
assert type(rfunc) == RFunc
dN = rfunc.N.degree()
dD = rfunc.D.degree()
out = []
if dN == dD + 1:
out += [rfunc.N // rfunc.D]
elif dN == dD:
out += [QPoly([rfunc.N[-1] / rfunc.D[-1]])]
elif dN < dD:
out += [QPoly([0])]
out += [QPoly([i]) for i in qpoly_roots(rfunc.D)]
return out
def kronecker_factorization(poly):
"""Modified kroneck factorization"""
deg = poly.degree()
fdeg = deg // 2
# Skip constant and linear terms, these could be factored using Kronecker's
# method but we will remove them before this.
if fdeg <= 1:
return [poly]
# TODO: Need a better way to choose points
# TODO: should search positive and negative and try to find values that
# evaluate to small numbers
points = [i for i in range(fdeg + 1)]
val_at_points = [poly(i) for i in points]
F = [reversed(factorization(e.n, negatives=True)) for e in val_at_points]
for evs in product(*F):
L = lagrange_interpolation(points, evs)
# Ignore factors with negative leading coefficient
if L[-1] < 0:
continue
# Ignore trivial factors
if L == QPoly([1]) or L == poly:
continue
# Skip possible factors with non-integer coefficients
if any(x.d != 1 for x in L):
continue
# Try the division
q, r = divmod(poly, L)
# Remainder must be zero
if r == QPoly([0]):
# all cofficients of the quotient must be integers
if all(x.d == 1 for x in q):
A = kronecker_factorization(L)
B = kronecker_factorization(q)
return A + B
return [poly]
def __mul__(self, other):
assert type(other) == int
if other == 0:
return QPolySum([QPoly([0])])
A = self.terms.copy()
B = A.copy()
for i in range(other - 1):
A.update(B)
return QPolySum(A)
def qpoly_roots(poly, den_lim=1000, iter_lim=1000):
P = poly.copy()
rr = rational_roots(poly)
roots = []
for i in rr:
roots.append(i)
P = P // QPoly([-i, 1])
intervals = sturm_root_isolation(P)
for i in intervals:
roots.append(bisection_method(P, i[0], i[1], den_lim, iter_lim))
return sorted(roots)
def __mul__(self, other):
A = self.terms.copy()
if type(other) == int:
return self * QPoly([other])
if type(other) == QPoly:
A.update([other])
elif type(other) == QPolyProd:
A.update(other.terms)
else:
return NotImplemented
return QPolyProd(A)
def sturm_sequence(poly):
"""Sequence of polynomials used for Sturm's Theorem"""
assert type(poly) == QPoly
p0 = poly
p1 = poly.derivative()
yield p0
while True:
if p1 == QPoly([0]):
break
p0, p1 = p1, -(p0 % p1)
yield p0
if len(p0) == 1:
break
def poly_egcd(P, Q):
"""Bézout's identity for two polynomials"""
assert type(P) == QPoly
assert type(Q) == QPoly
if Q.degree() > P.degree():
P, Q = Q, P
r0, r1 = P, Q
s0, s1 = 1, 0
t0, t1 = 0, 1
while r1 != QPoly([0]):
q = r0 // r1
r0, r1 = r1, r0 - q * r1
s0, s1 = s1, s0 - q * s1
t0, t1 = t1, t0 - q * t1
return r0.primitive_part, s0, t0
#
# norm = F[0]*C + F[1]*D
# print("normalizing factor",norm)
# C = C//norm
# D = D//norm
#
# t0 = RFunc( D*f, F[0] )
# t1 = RFunc( C*f, F[1] )
# out = f"{t0} + {t1}"
#
# print(out)
# print(t0+t1)
if __name__ == '__main__':
R = QPoly([-3, 1, 1])
approx_root = newtons_method(R, 2)
print(f"R = {R}")
print(
f"by Newton's method R has a root at approximately: {approx_root}\nwhich is {approx_root.digits(5)}"
)
print("\n\n")
approx_root = bisection_method(R, 0, 2, 10)
print(f"R = {R}")
print(
f"by the bisection method R has a root at approximately: {approx_root}\nwhich is {approx_root.digits(5)}"
)
print("\n\n")
def cast_to_poly(self):
"""Add everything together as a QPoly"""
out = QPoly([0])
for val, mul in self.terms.items():
out += val * mul
return out
# Then do some Kronecker factorization on what's left
out += kronecker_factorization(P)
out.sort(key=len, reverse=True)
return out
def factored_form(poly):
F = poly_factor(poly)
return QPolyProd(F)
if __name__ == '__main__':
S = QPoly([-1, 1]) * QPoly([5, -7, 3]) * QPoly([-1, 1]) * QPoly([7, 2]) * 3
print(S)
print("Factored version of S")
print(factored_form(S))
print()
print()
x = [1, 2, 3]
y = [1, 8, 27]
print(f"Lagrange Interpolation of\nx = {x}\ny = {y}")
print(lagrange_interpolation(x, y))
#
#
# print()
# print()
# S = QPoly( [-1,1] ) * QPoly( [3,3,3] ) * QPoly( [-1,2] ) * QPoly( [1,1,0,1] )
if len(i) == 1:
out.append(f"{i.pretty_name}^{{{pwr}}}")
else:
out.append(f"({i.pretty_name})^{{{pwr}}}")
J = "".join(out)
J = J.replace("$", "")
return f"${J}$"
# Things that are like attributes can be access as properties
pretty_name = property(_pretty_name)
if __name__ == '__main__':
P = QPoly([1, 2, 3])
Q = QPoly([6, -2])
R = QPoly([5])
S = QPoly([7])
sum_of_polys = QPolySum([P, S, Q, P, R, R, R])
print(sum_of_polys)
print(sum_of_polys.cast_to_poly())
print()
prod_of_polys1 = QPolyProd([P, S, R])
prod_of_polys2 = QPolyProd([P, S])
print(prod_of_polys1)
print(prod_of_polys1.cast_to_poly())
T = QPolySum([prod_of_polys1, prod_of_polys2])
def cast_to_poly(self):
"""Multiply everything together as a QPoly"""
out = QPoly([1])
for val, pwr in self.terms.items():
out *= val**pwr
return out
#########################
## TODO: Test convergents and semi-convergents
c = CFrac([5, 11, 7, 2])
c_minitests = [
(c, "[5; 11, 7, 2]"),
(c.as_rational(), "850/167"),
(c.pretty_name, "$5+\cfrac{1}{11+\cfrac{1}{7+\cfrac{1}{2}}}$"),
]
##################
## Polynonmials ##
##################
P = QPoly(["3/2", 0, 1, "11.6"])
Q = QPoly([-5, 1])
p_minitests = [(P, "58/5x^3 + x^2 + 3/2"), (Q, "x - 5"),
(P + Q, "58/5x^3 + x^2 + x - 7/2"),
(P * Q, "58/5x^4 - 57x^3 - 5x^2 + 3/2x - 15/2"), (P**0, "1"),
(P**2, "3364/25x^6 + 116/5x^5 + x^4 + 174/5x^3 + 3x^2 + 9/4"),
(P.integral(2), "29/10x^4 + 1/3x^3 + 3/2x + 2"),
(P.derivative(), "174/5x^2 + 2x"), (P.content, "1/10"),
(P.primitive_part, "116x^3 + 10x^2 + 15"),
(P.monic_part, "x^3 + 5/58x^2 + 15/116"),
(P // Q, "58/5x^2 + 59x + 295"), (P % Q, "2953/2"),
(P / Q, "(58/5x^3 + x^2 + 3/2) / (x - 5)")]
########################
## Rational Functions ##
