def mpc_sin_pi(z, prec, rnd=round_fast):
a, b = z
if b == fzero:
return mpf_sin_pi(a, prec, rnd), fzero
b = mpf_mul(b, mpf_pi(prec + 5), prec + 5)
if a == fzero:
return fzero, mpf_sinh(b, prec, rnd)
wp = prec + 6
c, s = mpf_cos_sin_pi(a, wp)
ch, sh = mpf_cosh_sinh(b, wp)
re = mpf_mul(s, ch, prec, rnd)
im = mpf_mul(c, sh, prec, rnd)
return re, im
def mpc_sin_pi(z, prec, rnd=round_fast):
a, b = z
if b == fzero:
return mpf_sin_pi(a, prec, rnd), fzero
b = mpf_mul(b, mpf_pi(prec + 5), prec + 5)
if a == fzero:
return fzero, mpf_sinh(b, prec, rnd)
wp = prec + 6
c, s = mpf_cos_sin_pi(a, wp)
ch, sh = mpf_cosh_sinh(b, wp)
re = mpf_mul(s, ch, prec, rnd)
im = mpf_mul(c, sh, prec, rnd)
return re, im
def mpf_gamma(x, prec, rounding=round_fast, p1=1):
"""
Computes the gamma function of a real floating-point argument.
With p1=0, computes a factorial instead.
"""
sign, man, exp, bc = x
if not man:
if x == finf:
return finf
if x == fninf or x == fnan:
return fnan
# More precision is needed for enormous x. TODO:
# use Stirling's formula + Euler-Maclaurin summation
size = exp + bc
if size > 5:
size = int(size * math.log(size,2))
wp = prec + max(0, size) + 15
if exp >= 0:
if sign or (p1 and not man):
raise ValueError("gamma function pole")
# A direct factorial is fastest
if exp + bc <= 10:
return from_int(ifac((man<<exp)-p1), prec, rounding)
reflect = sign or exp+bc < -1
if p1:
# Should be done exactly!
x = mpf_sub(x, fone)
# x < 0.25
if reflect:
# gamma = pi / (sin(pi*x) * gamma(1-x))
wp += 15
pix = mpf_mul(x, mpf_pi(wp), wp)
t = mpf_sin_pi(x, wp)
g = mpf_gamma(mpf_sub(fone, x), wp)
return mpf_div(pix, mpf_mul(t, g, wp), prec, rounding)
sprec, a, c = get_spouge_coefficients(wp)
s = spouge_sum_real(x, sprec, a, c)
# gamma = exp(log(x+a)*(x+0.5) - xpa) * s
xpa = mpf_add(x, from_int(a), wp)
logxpa = mpf_log(xpa, wp)
xph = mpf_add(x, fhalf, wp)
t = mpf_sub(mpf_mul(logxpa, xph, wp), xpa, wp)
t = mpf_mul(mpf_exp(t, wp), s, prec, rounding)
return t
def mpf_gamma(x, prec, rounding=round_fast, p1=1):
"""
Computes the gamma function of a real floating-point argument.
With p1=0, computes a factorial instead.
"""
sign, man, exp, bc = x
if not man:
if x == finf:
return finf
if x == fninf or x == fnan:
return fnan
# More precision is needed for enormous x. TODO:
# use Stirling's formula + Euler-Maclaurin summation
size = exp + bc
if size > 5:
size = int(size * math.log(size, 2))
wp = prec + max(0, size) + 15
if exp >= 0:
if sign or (p1 and not man):
raise ValueError("gamma function pole")
# A direct factorial is fastest
if exp + bc <= 10:
return from_int(int_fac((man << exp) - p1), prec, rounding)
reflect = sign or exp + bc < -1
if p1:
# Should be done exactly!
x = mpf_sub(x, fone)
# x < 0.25
if reflect:
# gamma = pi / (sin(pi*x) * gamma(1-x))
wp += 15
pix = mpf_mul(x, mpf_pi(wp), wp)
t = mpf_sin_pi(x, wp)
g = mpf_gamma(mpf_sub(fone, x), wp)
return mpf_div(pix, mpf_mul(t, g, wp), prec, rounding)
sprec, a, c = get_spouge_coefficients(wp)
s = spouge_sum_real(x, sprec, a, c)
# gamma = exp(log(x+a)*(x+0.5) - xpa) * s
xpa = mpf_add(x, from_int(a), wp)
logxpa = mpf_log(xpa, wp)
xph = mpf_add(x, fhalf, wp)
t = mpf_sub(mpf_mul(logxpa, xph, wp), xpa, wp)
t = mpf_mul(mpf_exp(t, wp), s, prec, rounding)
return t
def mpf_zeta(s, prec, rnd=round_fast, alt=0):
sign, man, exp, bc = s
if not man:
if s == fzero:
if alt:
return fhalf
else:
return mpf_neg(fhalf)
if s == finf:
return fone
return fnan
wp = prec + 20
# First term vanishes?
if (not sign) and (exp + bc > (math.log(wp,2) + 2)):
return mpf_perturb(fone, alt, prec, rnd)
# Optimize for integer arguments
elif exp >= 0:
if alt:
if s == fone:
return mpf_ln2(prec, rnd)
z = mpf_zeta_int(to_int(s), wp, negative_rnd[rnd])
q = mpf_sub(fone, mpf_pow(ftwo, mpf_sub(fone, s, wp), wp), wp)
return mpf_mul(z, q, prec, rnd)
else:
return mpf_zeta_int(to_int(s), prec, rnd)
# Negative: use the reflection formula
# Borwein only proves the accuracy bound for x >= 1/2. However, based on
# tests, the accuracy without reflection is quite good even some distance
# to the left of 1/2. XXX: verify this.
if sign:
# XXX: could use the separate refl. formula for Dirichlet eta
if alt:
q = mpf_sub(fone, mpf_pow(ftwo, mpf_sub(fone, s, wp), wp), wp)
return mpf_mul(mpf_zeta(s, wp), q, prec, rnd)
# XXX: -1 should be done exactly
y = mpf_sub(fone, s, 10*wp)
a = mpf_gamma(y, wp)
b = mpf_zeta(y, wp)
c = mpf_sin_pi(mpf_shift(s, -1), wp)
wp2 = wp + (exp+bc)
pi = mpf_pi(wp+wp2)
d = mpf_div(mpf_pow(mpf_shift(pi, 1), s, wp2), pi, wp2)
return mpf_mul(a,mpf_mul(b,mpf_mul(c,d,wp),wp),prec,rnd)
# Near pole
r = mpf_sub(fone, s, wp)
asign, aman, aexp, abc = mpf_abs(r)
pole_dist = -2*(aexp+abc)
if pole_dist > wp:
if alt:
return mpf_ln2(prec, rnd)
else:
q = mpf_neg(mpf_div(fone, r, wp))
return mpf_add(q, mpf_euler(wp), prec, rnd)
else:
wp += max(0, pole_dist)
t = MPZ_ZERO
#wp += 16 - (prec & 15)
# Use Borwein's algorithm
n = int(wp/2.54 + 5)
d = borwein_coefficients(n)
t = MPZ_ZERO
sf = to_fixed(s, wp)
for k in xrange(n):
u = from_man_exp(-sf*log_int_fixed(k+1, wp), -2*wp, wp)
esign, eman, eexp, ebc = mpf_exp(u, wp)
offset = eexp + wp
if offset >= 0:
w = ((d[k] - d[n]) * eman) << offset
else:
w = ((d[k] - d[n]) * eman) >> (-offset)
if k & 1:
t -= w
else:
t += w
t = t // (-d[n])
t = from_man_exp(t, -wp, wp)
if alt:
return mpf_pos(t, prec, rnd)
else:
q = mpf_sub(fone, mpf_pow(ftwo, mpf_sub(fone, s, wp), wp), wp)
return mpf_div(t, q, prec, rnd)
def mpf_zeta(s, prec, rnd=round_fast, alt=0):
sign, man, exp, bc = s
if not man:
if s == fzero:
if alt:
return fhalf
else:
return mpf_neg(fhalf)
if s == finf:
return fone
return fnan
wp = prec + 20
# First term vanishes?
if (not sign) and (exp + bc > (math.log(wp, 2) + 2)):
return mpf_perturb(fone, alt, prec, rnd)
# Optimize for integer arguments
elif exp >= 0:
if alt:
if s == fone:
return mpf_ln2(prec, rnd)
z = mpf_zeta_int(to_int(s), wp, negative_rnd[rnd])
q = mpf_sub(fone, mpf_pow(ftwo, mpf_sub(fone, s, wp), wp), wp)
return mpf_mul(z, q, prec, rnd)
else:
return mpf_zeta_int(to_int(s), prec, rnd)
# Negative: use the reflection formula
# Borwein only proves the accuracy bound for x >= 1/2. However, based on
# tests, the accuracy without reflection is quite good even some distance
# to the left of 1/2. XXX: verify this.
if sign:
# XXX: could use the separate refl. formula for Dirichlet eta
if alt:
q = mpf_sub(fone, mpf_pow(ftwo, mpf_sub(fone, s, wp), wp), wp)
return mpf_mul(mpf_zeta(s, wp), q, prec, rnd)
# XXX: -1 should be done exactly
y = mpf_sub(fone, s, 10 * wp)
a = mpf_gamma(y, wp)
b = mpf_zeta(y, wp)
c = mpf_sin_pi(mpf_shift(s, -1), wp)
wp2 = wp + (exp + bc)
pi = mpf_pi(wp + wp2)
d = mpf_div(mpf_pow(mpf_shift(pi, 1), s, wp2), pi, wp2)
return mpf_mul(a, mpf_mul(b, mpf_mul(c, d, wp), wp), prec, rnd)
t = MP_ZERO
#wp += 16 - (prec & 15)
# Use Borwein's algorithm
n = int(wp / 2.54 + 5)
d = borwein_coefficients(n)
t = MP_ZERO
sf = to_fixed(s, wp)
for k in xrange(n):
u = from_man_exp(-sf * log_int_fixed(k + 1, wp), -2 * wp, wp)
esign, eman, eexp, ebc = mpf_exp(u, wp)
offset = eexp + wp
if offset >= 0:
w = ((d[k] - d[n]) * eman) << offset
else:
w = ((d[k] - d[n]) * eman) >> (-offset)
if k & 1:
t -= w
else:
t += w
t = t // (-d[n])
t = from_man_exp(t, -wp, wp)
if alt:
return mpf_pos(t, prec, rnd)
else:
q = mpf_sub(fone, mpf_pow(ftwo, mpf_sub(fone, s, wp), wp), wp)
return mpf_div(t, q, prec, rnd)
