def mpf_psi0(x, prec, rnd=round_fast):
"""
Computation of the digamma function (psi function of order 0)
of a real argument.
"""
sign, man, exp, bc = x
wp = prec + 10
if not man:
if x == finf:
return x
if x == fninf or x == fnan:
return fnan
if x == fzero or (exp >= 0 and sign):
raise ValueError("polygamma pole")
# Reflection formula
if sign and exp + bc > 3:
c, s = mpf_cos_sin_pi(x, wp)
q = mpf_mul(mpf_div(c, s, wp), mpf_pi(wp), wp)
p = mpf_psi0(mpf_sub(fone, x, wp), wp)
return mpf_sub(p, q, prec, rnd)
# The logarithmic term is accurate enough
if (not sign) and bc + exp > wp:
return mpf_log(mpf_sub(x, fone, wp), prec, rnd)
# Initial recurrence to obtain a large enough x
m = to_int(x)
n = int(0.11 * wp) + 2
s = MP_ZERO
x = to_fixed(x, wp)
one = MP_ONE << wp
if m < n:
for k in xrange(m, n):
s -= (one << wp) // x
x += one
x -= one
# Logarithmic term
s += to_fixed(mpf_log(from_man_exp(x, -wp, wp), wp), wp)
# Endpoint term in Euler-Maclaurin expansion
s += (one << wp) // (2 * x)
# Euler-Maclaurin remainder sum
x2 = (x * x) >> wp
t = one
prev = 0
k = 1
while 1:
t = (t * x2) >> wp
bsign, bman, bexp, bbc = mpf_bernoulli(2 * k, wp)
offset = bexp + 2 * wp
if offset >= 0:
term = (bman << offset) // (t * (2 * k))
else:
term = (bman >> (-offset)) // (t * (2 * k))
if k & 1:
s -= term
else:
s += term
if k > 2 and term >= prev:
break
prev = term
k += 1
return from_man_exp(s, -wp, wp, rnd)
def mpf_psi0(x, prec, rnd=round_fast):
"""
Computation of the digamma function (psi function of order 0)
of a real argument.
"""
sign, man, exp, bc = x
wp = prec + 10
if not man:
if x == finf: return x
if x == fninf or x == fnan: return fnan
if x == fzero or (exp >= 0 and sign):
raise ValueError("polygamma pole")
# Reflection formula
if sign and exp + bc > 3:
c, s = mpf_cos_sin_pi(x, wp)
q = mpf_mul(mpf_div(c, s, wp), mpf_pi(wp), wp)
p = mpf_psi0(mpf_sub(fone, x, wp), wp)
return mpf_sub(p, q, prec, rnd)
# The logarithmic term is accurate enough
if (not sign) and bc + exp > wp:
return mpf_log(mpf_sub(x, fone, wp), prec, rnd)
# Initial recurrence to obtain a large enough x
m = to_int(x)
n = int(0.11 * wp) + 2
s = MP_ZERO
x = to_fixed(x, wp)
one = MP_ONE << wp
if m < n:
for k in xrange(m, n):
s -= (one << wp) // x
x += one
x -= one
# Logarithmic term
s += to_fixed(mpf_log(from_man_exp(x, -wp, wp), wp), wp)
# Endpoint term in Euler-Maclaurin expansion
s += (one << wp) // (2 * x)
# Euler-Maclaurin remainder sum
x2 = (x * x) >> wp
t = one
prev = 0
k = 1
while 1:
t = (t * x2) >> wp
bsign, bman, bexp, bbc = mpf_bernoulli(2 * k, wp)
offset = (bexp + 2 * wp)
if offset >= 0: term = (bman << offset) // (t * (2 * k))
else: term = (bman >> (-offset)) // (t * (2 * k))
if k & 1: s -= term
else: s += term
if k > 2 and term >= prev:
break
prev = term
k += 1
return from_man_exp(s, -wp, wp, rnd)
def glaisher_fixed(prec):
wp = prec + 30
# Number of direct terms to sum before applying the Euler-Maclaurin
# formula to the tail. TODO: choose more intelligently
N = int(0.33*prec + 5)
ONE = MPZ_ONE << wp
# Euler-Maclaurin, step 1: sum log(k)/k**2 for k from 2 to N-1
s = MPZ_ZERO
for k in range(2, N):
#print k, N
s += log_int_fixed(k, wp) // k**2
logN = log_int_fixed(N, wp)
#logN = to_fixed(mpf_log(from_int(N), wp+20), wp)
# E-M step 2: integral of log(x)/x**2 from N to inf
s += (ONE + logN) // N
# E-M step 3: endpoint correction term f(N)/2
s += logN // (N**2 * 2)
# E-M step 4: the series of derivatives
pN = N**3
a = 1
b = -2
j = 3
fac = from_int(2)
k = 1
while 1:
# D(2*k-1) * B(2*k) / fac(2*k) [D(n) = nth derivative]
D = ((a << wp) + b*logN) // pN
D = from_man_exp(D, -wp)
B = mpf_bernoulli(2*k, wp)
term = mpf_mul(B, D, wp)
term = mpf_div(term, fac, wp)
term = to_fixed(term, wp)
if abs(term) < 100:
break
#if not k % 10:
# print k, math.log(int(abs(term)), 10)
s -= term
# Advance derivative twice
a, b, pN, j = b-a*j, -j*b, pN*N, j+1
a, b, pN, j = b-a*j, -j*b, pN*N, j+1
k += 1
fac = mpf_mul_int(fac, (2*k)*(2*k-1), wp)
# A = exp((6*s/pi**2 + log(2*pi) + euler)/12)
pi = pi_fixed(wp)
s *= 6
s = (s << wp) // (pi**2 >> wp)
s += euler_fixed(wp)
s += to_fixed(mpf_log(from_man_exp(2*pi, -wp), wp), wp)
s //= 12
A = mpf_exp(from_man_exp(s, -wp), wp)
return to_fixed(A, prec)
def glaisher_fixed(prec):
wp = prec + 30
# Number of direct terms to sum before applying the Euler-Maclaurin
# formula to the tail. TODO: choose more intelligently
N = int(0.33 * prec + 5)
ONE = MP_ONE << wp
# Euler-Maclaurin, step 1: sum log(k)/k**2 for k from 2 to N-1
s = MP_ZERO
for k in range(2, N):
#print k, N
s += log_int_fixed(k, wp) // k**2
logN = log_int_fixed(N, wp)
#logN = to_fixed(mpf_log(from_int(N), wp+20), wp)
# E-M step 2: integral of log(x)/x**2 from N to inf
s += (ONE + logN) // N
# E-M step 3: endpoint correction term f(N)/2
s += logN // (N**2 * 2)
# E-M step 4: the series of derivatives
pN = N**3
a = 1
b = -2
j = 3
fac = from_int(2)
k = 1
while 1:
# D(2*k-1) * B(2*k) / fac(2*k) [D(n) = nth derivative]
D = ((a << wp) + b * logN) // pN
D = from_man_exp(D, -wp)
B = mpf_bernoulli(2 * k, wp)
term = mpf_mul(B, D, wp)
term = mpf_div(term, fac, wp)
term = to_fixed(term, wp)
if abs(term) < 100:
break
#if not k % 10:
# print k, math.log(int(abs(term)), 10)
s -= term
# Advance derivative twice
a, b, pN, j = b - a * j, -j * b, pN * N, j + 1
a, b, pN, j = b - a * j, -j * b, pN * N, j + 1
k += 1
fac = mpf_mul_int(fac, (2 * k) * (2 * k - 1), wp)
# A = exp((6*s/pi**2 + log(2*pi) + euler)/12)
pi = pi_fixed(wp)
s *= 6
s = (s << wp) // (pi**2 >> wp)
s += euler_fixed(wp)
s += to_fixed(mpf_log(from_man_exp(2 * pi, -wp), wp), wp)
s //= 12
A = mpf_exp(from_man_exp(s, -wp), wp)
return to_fixed(A, prec)
def mertens_fixed(prec):
wp = prec + 20
m = 2
s = mpf_euler(wp)
while 1:
t = mpf_zeta_int(m, wp)
if t == fone:
break
t = mpf_log(t, wp)
t = mpf_mul_int(t, moebius(m), wp)
t = mpf_div(t, from_int(m), wp)
s = mpf_add(s, t)
m += 1
return to_fixed(s, prec)
def mertens_fixed(prec):
wp = prec + 20
m = 2
s = mpf_euler(wp)
while 1:
t = mpf_zeta_int(m, wp)
if t == fone:
break
t = mpf_log(t, wp)
t = mpf_mul_int(t, moebius(m), wp)
t = mpf_div(t, from_int(m), wp)
s = mpf_add(s, t)
m += 1
return to_fixed(s, prec)
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, bc - exp + 2)
# 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), 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(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_ei(x, prec, rnd=round_fast, e1=False):
if e1:
x = mpf_neg(x)
sign, man, exp, bc = x
if e1 and not sign:
if x == fzero:
return finf
raise ComplexResult("E1(x) for x < 0")
if man:
xabs = 0, man, exp, bc
xmag = exp+bc
wp = prec + 20
can_use_asymp = xmag > wp
if not can_use_asymp:
if exp >= 0:
xabsint = man << exp
else:
xabsint = man >> (-exp)
can_use_asymp = xabsint > int(wp*0.693) + 10
if can_use_asymp:
if xmag > wp:
v = fone
else:
v = from_man_exp(ei_asymptotic(to_fixed(x, wp), wp), -wp)
v = mpf_mul(v, mpf_exp(x, wp), wp)
v = mpf_div(v, x, prec, rnd)
else:
wp += 2*int(to_int(xabs))
u = to_fixed(x, wp)
v = ei_taylor(u, wp) + euler_fixed(wp)
t1 = from_man_exp(v,-wp)
t2 = mpf_log(xabs,wp)
v = mpf_add(t1, t2, prec, rnd)
else:
if x == fzero: v = fninf
elif x == finf: v = finf
elif x == fninf: v = fzero
else: v = fnan
if e1:
v = mpf_neg(v)
return v
def mpf_ei(x, prec, rnd=round_fast, e1=False):
if e1:
x = mpf_neg(x)
sign, man, exp, bc = x
if e1 and not sign:
if x == fzero:
return finf
raise ComplexResult("E1(x) for x < 0")
if man:
xabs = 0, man, exp, bc
xmag = exp + bc
wp = prec + 20
can_use_asymp = xmag > wp
if not can_use_asymp:
if exp >= 0:
xabsint = man << exp
else:
xabsint = man >> (-exp)
can_use_asymp = xabsint > int(wp * 0.693) + 10
if can_use_asymp:
if xmag > wp:
v = fone
else:
v = from_man_exp(ei_asymptotic(to_fixed(x, wp), wp), -wp)
v = mpf_mul(v, mpf_exp(x, wp), wp)
v = mpf_div(v, x, prec, rnd)
else:
wp += 2 * int(to_int(xabs))
u = to_fixed(x, wp)
v = ei_taylor(u, wp) + euler_fixed(wp)
t1 = from_man_exp(v, -wp)
t2 = mpf_log(xabs, wp)
v = mpf_add(t1, t2, prec, rnd)
else:
if x == fzero: v = fninf
elif x == finf: v = finf
elif x == fninf: v = fzero
else: v = fnan
if e1:
v = mpf_neg(v)
return v
def acos_asin(z, prec, rnd, n):
""" complex acos for n = 0, asin for n = 1
The algorithm is described in
T.E. Hull, T.F. Fairgrieve and P.T.P. Tang
'Implementing the Complex Arcsine and Arcosine Functions
using Exception Handling',
ACM Trans. on Math. Software Vol. 23 (1997), p299
The complex acos and asin can be defined as
acos(z) = acos(beta) - I*sign(a)* log(alpha + sqrt(alpha**2 -1))
asin(z) = asin(beta) + I*sign(a)* log(alpha + sqrt(alpha**2 -1))
where z = a + I*b
alpha = (1/2)*(r + s); beta = (1/2)*(r - s) = a/alpha
r = sqrt((a+1)**2 + y**2); s = sqrt((a-1)**2 + y**2)
These expressions are rewritten in different ways in different
regions, delimited by two crossovers alpha_crossover and beta_crossover,
and by abs(a) <= 1, in order to improve the numerical accuracy.
"""
a, b = z
wp = prec + 10
# special cases with real argument
if b == fzero:
am = mpf_sub(fone, mpf_abs(a), wp)
# case abs(a) <= 1
if not am[0]:
if n == 0:
return mpf_acos(a, prec, rnd), fzero
else:
return mpf_asin(a, prec, rnd), fzero
# cases abs(a) > 1
else:
# case a < -1
if a[0]:
pi = mpf_pi(prec, rnd)
c = mpf_acosh(mpf_neg(a), prec, rnd)
if n == 0:
return pi, mpf_neg(c)
else:
return mpf_neg(mpf_shift(pi, -1)), c
# case a > 1
else:
c = mpf_acosh(a, prec, rnd)
if n == 0:
return fzero, c
else:
pi = mpf_pi(prec, rnd)
return mpf_shift(pi, -1), mpf_neg(c)
asign = bsign = 0
if a[0]:
a = mpf_neg(a)
asign = 1
if b[0]:
b = mpf_neg(b)
bsign = 1
am = mpf_sub(fone, a, wp)
ap = mpf_add(fone, a, wp)
r = mpf_hypot(ap, b, wp)
s = mpf_hypot(am, b, wp)
alpha = mpf_shift(mpf_add(r, s, wp), -1)
beta = mpf_div(a, alpha, wp)
b2 = mpf_mul(b, b, wp)
# case beta <= beta_crossover
if not mpf_sub(beta_crossover, beta, wp)[0]:
if n == 0:
re = mpf_acos(beta, wp)
else:
re = mpf_asin(beta, wp)
else:
# to compute the real part in this region use the identity
# asin(beta) = atan(beta/sqrt(1-beta**2))
# beta/sqrt(1-beta**2) = (alpha + a) * (alpha - a)
# alpha + a is numerically accurate; alpha - a can have
# cancellations leading to numerical inaccuracies, so rewrite
# it in differente ways according to the region
Ax = mpf_add(alpha, a, wp)
# case a <= 1
if not am[0]:
# c = b*b/(r + (a+1)); d = (s + (1-a))
# alpha - a = (1/2)*(c + d)
# case n=0: re = atan(sqrt((1/2) * Ax * (c + d))/a)
# case n=1: re = atan(a/sqrt((1/2) * Ax * (c + d)))
c = mpf_div(b2, mpf_add(r, ap, wp), wp)
d = mpf_add(s, am, wp)
re = mpf_shift(mpf_mul(Ax, mpf_add(c, d, wp), wp), -1)
if n == 0:
re = mpf_atan(mpf_div(mpf_sqrt(re, wp), a, wp), wp)
else:
re = mpf_atan(mpf_div(a, mpf_sqrt(re, wp), wp), wp)
else:
# c = Ax/(r + (a+1)); d = Ax/(s - (1-a))
# alpha - a = (1/2)*(c + d)
# case n = 0: re = atan(b*sqrt(c + d)/2/a)
# case n = 1: re = atan(a/(b*sqrt(c + d)/2)
c = mpf_div(Ax, mpf_add(r, ap, wp), wp)
d = mpf_div(Ax, mpf_sub(s, am, wp), wp)
re = mpf_shift(mpf_add(c, d, wp), -1)
re = mpf_mul(b, mpf_sqrt(re, wp), wp)
if n == 0:
re = mpf_atan(mpf_div(re, a, wp), wp)
else:
re = mpf_atan(mpf_div(a, re, wp), wp)
# to compute alpha + sqrt(alpha**2 - 1), if alpha <= alpha_crossover
# replace it with 1 + Am1 + sqrt(Am1*(alpha+1)))
# where Am1 = alpha -1
# if alpha <= alpha_crossover:
if not mpf_sub(alpha_crossover, alpha, wp)[0]:
c1 = mpf_div(b2, mpf_add(r, ap, wp), wp)
# case a < 1
if mpf_neg(am)[0]:
# Am1 = (1/2) * (b*b/(r + (a+1)) + b*b/(s + (1-a))
c2 = mpf_add(s, am, wp)
c2 = mpf_div(b2, c2, wp)
Am1 = mpf_shift(mpf_add(c1, c2, wp), -1)
else:
# Am1 = (1/2) * (b*b/(r + (a+1)) + (s - (1-a)))
c2 = mpf_sub(s, am, wp)
Am1 = mpf_shift(mpf_add(c1, c2, wp), -1)
# im = log(1 + Am1 + sqrt(Am1*(alpha+1)))
im = mpf_mul(Am1, mpf_add(alpha, fone, wp), wp)
im = mpf_log(mpf_add(fone, mpf_add(Am1, mpf_sqrt(im, wp), wp), wp), wp)
else:
# im = log(alpha + sqrt(alpha*alpha - 1))
im = mpf_sqrt(mpf_sub(mpf_mul(alpha, alpha, wp), fone, wp), wp)
im = mpf_log(mpf_add(alpha, im, wp), wp)
if asign:
if n == 0:
re = mpf_sub(mpf_pi(wp), re, wp)
else:
re = mpf_neg(re)
if not bsign and n == 0:
im = mpf_neg(im)
if bsign and n == 1:
im = mpf_neg(im)
re = normalize(re[0], re[1], re[2], re[3], prec, rnd)
im = normalize(im[0], im[1], im[2], im[3], prec, rnd)
return re, im
def mpi_log(s, prec):
sa, sb = s
# log is monotonous
a = mpf_log(sa, prec, round_floor)
b = mpf_log(sb, prec, round_ceiling)
return a, b
def mpc_log(z, prec, rnd=round_fast):
return mpf_log(mpc_abs(z, prec, rnd), prec, rnd), mpc_arg(z, prec, rnd)
def acos_asin(z, prec, rnd, n):
""" complex acos for n = 0, asin for n = 1
The algorithm is described in
T.E. Hull, T.F. Fairgrieve and P.T.P. Tang
'Implementing the Complex Arcsine and Arcosine Functions
using Exception Handling',
ACM Trans. on Math. Software Vol. 23 (1997), p299
The complex acos and asin can be defined as
acos(z) = acos(beta) - I*sign(a)* log(alpha + sqrt(alpha**2 -1))
asin(z) = asin(beta) + I*sign(a)* log(alpha + sqrt(alpha**2 -1))
where z = a + I*b
alpha = (1/2)*(r + s); beta = (1/2)*(r - s) = a/alpha
r = sqrt((a+1)**2 + y**2); s = sqrt((a-1)**2 + y**2)
These expressions are rewritten in different ways in different
regions, delimited by two crossovers alpha_crossover and beta_crossover,
and by abs(a) <= 1, in order to improve the numerical accuracy.
"""
a, b = z
wp = prec + 10
# special cases with real argument
if b == fzero:
am = mpf_sub(fone, mpf_abs(a), wp)
# case abs(a) <= 1
if not am[0]:
if n == 0:
return mpf_acos(a, prec, rnd), fzero
else:
return mpf_asin(a, prec, rnd), fzero
# cases abs(a) > 1
else:
# case a < -1
if a[0]:
pi = mpf_pi(prec, rnd)
c = mpf_acosh(mpf_neg(a), prec, rnd)
if n == 0:
return pi, mpf_neg(c)
else:
return mpf_neg(mpf_shift(pi, -1)), c
# case a > 1
else:
c = mpf_acosh(a, prec, rnd)
if n == 0:
return fzero, c
else:
pi = mpf_pi(prec, rnd)
return mpf_shift(pi, -1), mpf_neg(c)
asign = bsign = 0
if a[0]:
a = mpf_neg(a)
asign = 1
if b[0]:
b = mpf_neg(b)
bsign = 1
am = mpf_sub(fone, a, wp)
ap = mpf_add(fone, a, wp)
r = mpf_hypot(ap, b, wp)
s = mpf_hypot(am, b, wp)
alpha = mpf_shift(mpf_add(r, s, wp), -1)
beta = mpf_div(a, alpha, wp)
b2 = mpf_mul(b, b, wp)
# case beta <= beta_crossover
if not mpf_sub(beta_crossover, beta, wp)[0]:
if n == 0:
re = mpf_acos(beta, wp)
else:
re = mpf_asin(beta, wp)
else:
# to compute the real part in this region use the identity
# asin(beta) = atan(beta/sqrt(1-beta**2))
# beta/sqrt(1-beta**2) = (alpha + a) * (alpha - a)
# alpha + a is numerically accurate; alpha - a can have
# cancellations leading to numerical inaccuracies, so rewrite
# it in differente ways according to the region
Ax = mpf_add(alpha, a, wp)
# case a <= 1
if not am[0]:
# c = b*b/(r + (a+1)); d = (s + (1-a))
# alpha - a = (1/2)*(c + d)
# case n=0: re = atan(sqrt((1/2) * Ax * (c + d))/a)
# case n=1: re = atan(a/sqrt((1/2) * Ax * (c + d)))
c = mpf_div(b2, mpf_add(r, ap, wp), wp)
d = mpf_add(s, am, wp)
re = mpf_shift(mpf_mul(Ax, mpf_add(c, d, wp), wp), -1)
if n == 0:
re = mpf_atan(mpf_div(mpf_sqrt(re, wp), a, wp), wp)
else:
re = mpf_atan(mpf_div(a, mpf_sqrt(re, wp), wp), wp)
else:
# c = Ax/(r + (a+1)); d = Ax/(s - (1-a))
# alpha - a = (1/2)*(c + d)
# case n = 0: re = atan(b*sqrt(c + d)/2/a)
# case n = 1: re = atan(a/(b*sqrt(c + d)/2)
c = mpf_div(Ax, mpf_add(r, ap, wp), wp)
d = mpf_div(Ax, mpf_sub(s, am, wp), wp)
re = mpf_shift(mpf_add(c, d, wp), -1)
re = mpf_mul(b, mpf_sqrt(re, wp), wp)
if n == 0:
re = mpf_atan(mpf_div(re, a, wp), wp)
else:
re = mpf_atan(mpf_div(a, re, wp), wp)
# to compute alpha + sqrt(alpha**2 - 1), if alpha <= alpha_crossover
# replace it with 1 + Am1 + sqrt(Am1*(alpha+1)))
# where Am1 = alpha -1
# if alpha <= alpha_crossover:
if not mpf_sub(alpha_crossover, alpha, wp)[0]:
c1 = mpf_div(b2, mpf_add(r, ap, wp), wp)
# case a < 1
if mpf_neg(am)[0]:
# Am1 = (1/2) * (b*b/(r + (a+1)) + b*b/(s + (1-a))
c2 = mpf_add(s, am, wp)
c2 = mpf_div(b2, c2, wp)
Am1 = mpf_shift(mpf_add(c1, c2, wp), -1)
else:
# Am1 = (1/2) * (b*b/(r + (a+1)) + (s - (1-a)))
c2 = mpf_sub(s, am, wp)
Am1 = mpf_shift(mpf_add(c1, c2, wp), -1)
# im = log(1 + Am1 + sqrt(Am1*(alpha+1)))
im = mpf_mul(Am1, mpf_add(alpha, fone, wp), wp)
im = mpf_log(mpf_add(fone, mpf_add(Am1, mpf_sqrt(im, wp), wp), wp), wp)
else:
# im = log(alpha + sqrt(alpha*alpha - 1))
im = mpf_sqrt(mpf_sub(mpf_mul(alpha, alpha, wp), fone, wp), wp)
im = mpf_log(mpf_add(alpha, im, wp), wp)
if asign:
if n == 0:
re = mpf_sub(mpf_pi(wp), re, wp)
else:
re = mpf_neg(re)
if not bsign and n == 0:
im = mpf_neg(im)
if bsign and n == 1:
im = mpf_neg(im)
re = normalize(re[0], re[1], re[2], re[3], prec, rnd)
im = normalize(im[0], im[1], im[2], im[3], prec, rnd)
return re, im
def mpf_ci_si(x, prec, rnd=round_fast, which=2):
"""
Calculation of Ci(x), Si(x) for real x.
which = 0 -- returns (Ci(x), -)
which = 1 -- returns (Si(x), -)
which = 2 -- returns (Ci(x), Si(x))
Note: if x < 0, Ci(x) needs an additional imaginary term, pi*i.
"""
wp = prec + 20
sign, man, exp, bc = x
ci, si = None, None
if not man:
if x == fzero:
return (fninf, fzero)
if x == fnan:
return (x, x)
ci = fzero
if which != 0:
if x == finf:
si = mpf_shift(mpf_pi(prec, rnd), -1)
if x == fninf:
si = mpf_neg(mpf_shift(mpf_pi(prec, negative_rnd[rnd]), -1))
return (ci, si)
# For small x: Ci(x) ~ euler + log(x), Si(x) ~ x
mag = exp+bc
if mag < -wp:
if which != 0:
si = mpf_perturb(x, 1-sign, prec, rnd)
if which != 1:
y = mpf_euler(wp)
xabs = mpf_abs(x)
ci = mpf_add(y, mpf_log(xabs, wp), prec, rnd)
return ci, si
# For huge x: Ci(x) ~ sin(x)/x, Si(x) ~ pi/2
elif mag > wp:
if which != 0:
if sign:
si = mpf_neg(mpf_pi(prec, negative_rnd[rnd]))
else:
si = mpf_pi(prec, rnd)
si = mpf_shift(si, -1)
if which != 1:
ci = mpf_div(mpf_sin(x, wp), x, prec, rnd)
return ci, si
else:
wp += abs(mag)
# Use an asymptotic series? The smallest value of n!/x^n
# occurs for n ~ x, where the magnitude is ~ exp(-x).
asymptotic = mag-1 > math.log(wp, 2)
# Case 1: convergent series near 0
if not asymptotic:
if which != 0:
si = mpf_pos(mpf_ci_si_taylor(x, wp, 1), prec, rnd)
if which != 1:
ci = mpf_ci_si_taylor(x, wp, 0)
ci = mpf_add(ci, mpf_euler(wp), wp)
ci = mpf_add(ci, mpf_log(mpf_abs(x), wp), prec, rnd)
return ci, si
x = mpf_abs(x)
# Case 2: asymptotic series for x >> 1
xf = to_fixed(x, wp)
xr = (MPZ_ONE<<(2*wp)) // xf # 1/x
s1 = (MPZ_ONE << wp)
s2 = xr
t = xr
k = 2
while t:
t = -t
t = (t*xr*k)>>wp
k += 1
s1 += t
t = (t*xr*k)>>wp
k += 1
s2 += t
s1 = from_man_exp(s1, -wp)
s2 = from_man_exp(s2, -wp)
s1 = mpf_div(s1, x, wp)
s2 = mpf_div(s2, x, wp)
cos, sin = mpf_cos_sin(x, wp)
# Ci(x) = sin(x)*s1-cos(x)*s2
# Si(x) = pi/2-cos(x)*s1-sin(x)*s2
if which != 0:
si = mpf_add(mpf_mul(cos, s1), mpf_mul(sin, s2), wp)
si = mpf_sub(mpf_shift(mpf_pi(wp), -1), si, wp)
if sign:
si = mpf_neg(si)
si = mpf_pos(si, prec, rnd)
if which != 1:
ci = mpf_sub(mpf_mul(sin, s1), mpf_mul(cos, s2), prec, rnd)
return ci, si
def mpf_ci_si(x, prec, rnd=round_fast, which=2):
"""
Calculation of Ci(x), Si(x) for real x.
which = 0 -- returns (Ci(x), -)
which = 1 -- returns (Si(x), -)
which = 2 -- returns (Ci(x), Si(x))
Note: if x < 0, Ci(x) needs an additional imaginary term, pi*i.
"""
wp = prec + 20
sign, man, exp, bc = x
ci, si = None, None
if not man:
if x == fzero:
return (fninf, fzero)
if x == fnan:
return (x, x)
ci = fzero
if which != 0:
if x == finf:
si = mpf_shift(mpf_pi(prec, rnd), -1)
if x == fninf:
si = mpf_neg(mpf_shift(mpf_pi(prec, negative_rnd[rnd]), -1))
return (ci, si)
# For small x: Ci(x) ~ euler + log(x), Si(x) ~ x
mag = exp + bc
if mag < -wp:
if which != 0:
si = mpf_perturb(x, 1 - sign, prec, rnd)
if which != 1:
y = mpf_euler(wp)
xabs = mpf_abs(x)
ci = mpf_add(y, mpf_log(xabs, wp), prec, rnd)
return ci, si
# For huge x: Ci(x) ~ sin(x)/x, Si(x) ~ pi/2
elif mag > wp:
if which != 0:
if sign:
si = mpf_neg(mpf_pi(prec, negative_rnd[rnd]))
else:
si = mpf_pi(prec, rnd)
si = mpf_shift(si, -1)
if which != 1:
ci = mpf_div(mpf_sin(x, wp), x, prec, rnd)
return ci, si
else:
wp += abs(mag)
# Use an asymptotic series? The smallest value of n!/x^n
# occurs for n ~ x, where the magnitude is ~ exp(-x).
asymptotic = mag - 1 > math.log(wp, 2)
# Case 1: convergent series near 0
if not asymptotic:
if which != 0:
si = mpf_pos(mpf_ci_si_taylor(x, wp, 1), prec, rnd)
if which != 1:
ci = mpf_ci_si_taylor(x, wp, 0)
ci = mpf_add(ci, mpf_euler(wp), wp)
ci = mpf_add(ci, mpf_log(mpf_abs(x), wp), prec, rnd)
return ci, si
x = mpf_abs(x)
# Case 2: asymptotic series for x >> 1
xf = to_fixed(x, wp)
xr = (MP_ONE << (2 * wp)) // xf # 1/x
s1 = (MP_ONE << wp)
s2 = xr
t = xr
k = 2
while t:
t = -t
t = (t * xr * k) >> wp
k += 1
s1 += t
t = (t * xr * k) >> wp
k += 1
s2 += t
s1 = from_man_exp(s1, -wp)
s2 = from_man_exp(s2, -wp)
s1 = mpf_div(s1, x, wp)
s2 = mpf_div(s2, x, wp)
cos, sin = cos_sin(x, wp)
# Ci(x) = sin(x)*s1-cos(x)*s2
# Si(x) = pi/2-cos(x)*s1-sin(x)*s2
if which != 0:
si = mpf_add(mpf_mul(cos, s1), mpf_mul(sin, s2), wp)
si = mpf_sub(mpf_shift(mpf_pi(wp), -1), si, wp)
if sign:
si = mpf_neg(si)
si = mpf_pos(si, prec, rnd)
if which != 1:
ci = mpf_sub(mpf_mul(sin, s1), mpf_mul(cos, s2), prec, rnd)
return ci, si
def mpi_log(s, prec):
sa, sb = s
# log is monotonous
a = mpf_log(sa, prec, round_floor)
b = mpf_log(sb, prec, round_ceiling)
return a, b
def mpc_log(z, prec, rnd=round_fast):
return mpf_log(mpc_abs(z, prec, rnd), prec, rnd), mpc_arg(z, prec, rnd)
