def mpf_atan2(y, x, prec, rnd=round_fast): xsign, xman, xexp, xbc = x ysign, yman, yexp, ybc = y if not yman: if y == fnan or x == fnan: return fnan if mpf_sign(x) >= 0: return fzero return mpf_pi(prec, rnd) if ysign: return mpf_neg(mpf_atan2(mpf_neg(y), x, prec, rnd)) if not xman: if x == fnan: return fnan if x == finf: return fzero if x == fninf: return mpf_pi(prec, rnd) if not yman: return fzero return mpf_shift(mpf_pi(prec, rnd), -1) tquo = mpf_atan(mpf_div(y, x, prec+4), prec+4) if xsign: return mpf_add(mpf_pi(prec+4), tquo, prec, rnd) else: return mpf_pos(tquo, prec, rnd)
def mpf_atan2(y, x, prec, rnd=round_fast): xsign, xman, xexp, xbc = x ysign, yman, yexp, ybc = y if not yman: if y == fnan or x == fnan: return fnan if mpf_sign(x) >= 0: return fzero return mpf_pi(prec, rnd) if ysign: return mpf_neg(mpf_atan2(mpf_neg(y), x, prec, rnd)) if not xman: if x == fnan: return fnan if x == finf: return fzero if x == fninf: return mpf_pi(prec, rnd) if not yman: return fzero return mpf_shift(mpf_pi(prec, rnd), -1) tquo = mpf_atan(mpf_div(y, x, prec + 4), prec + 4) if xsign: return mpf_add(mpf_pi(prec + 4), tquo, prec, rnd) else: return mpf_pos(tquo, prec, rnd)
def twinprime_fixed(prec): def I(n): return sum( moebius(d) << (n // d) for d in xrange(1, n + 1) if not n % d) // n wp = 2 * prec + 30 res = fone primes = [from_rational(1, p, wp) for p in [2, 3, 5, 7]] ppowers = [mpf_mul(p, p, wp) for p in primes] n = 2 while 1: a = mpf_zeta_int(n, wp) for i in range(4): a = mpf_mul(a, mpf_sub(fone, ppowers[i]), wp) ppowers[i] = mpf_mul(ppowers[i], primes[i], wp) a = mpf_pow_int(a, -I(n), wp) if mpf_pos(a, prec + 10, 'n') == fone: break #from libmpf import to_str #print n, to_str(mpf_sub(fone, a), 6) res = mpf_mul(res, a, wp) n += 1 res = mpf_mul(res, from_int(3 * 15 * 35), wp) res = mpf_div(res, from_int(4 * 16 * 36), wp) return to_fixed(res, prec)
def mpf_atan2(y, x, prec, rnd=round_fast): xsign, xman, xexp, xbc = x ysign, yman, yexp, ybc = y if not yman: if y == fzero and x != fnan: if mpf_sign(x) >= 0: return fzero return mpf_pi(prec, rnd) if y in (finf, fninf): if x in (finf, fninf): return fnan # pi/2 if y == finf: return mpf_shift(mpf_pi(prec, rnd), -1) # -pi/2 return mpf_neg(mpf_shift(mpf_pi(prec, negative_rnd[rnd]), -1)) return fnan if ysign: return mpf_neg(mpf_atan2(mpf_neg(y), x, prec, negative_rnd[rnd])) if not xman: if x == fnan: return fnan if x == finf: return fzero if x == fninf: return mpf_pi(prec, rnd) if y == fzero: return fzero return mpf_shift(mpf_pi(prec, rnd), -1) tquo = mpf_atan(mpf_div(y, x, prec+4), prec+4) if xsign: return mpf_add(mpf_pi(prec+4), tquo, prec, rnd) else: return mpf_pos(tquo, prec, rnd)
def mpf_bernoulli_huge(n, prec, rnd=None): wp = prec + 10 piprec = wp + int(math.log(n, 2)) v = mpf_gamma_int(n + 1, wp) v = mpf_mul(v, mpf_zeta_int(n, wp), wp) v = mpf_mul(v, mpf_pow_int(mpf_pi(piprec), -n, wp)) v = mpf_shift(v, 1 - n) if not n & 3: v = mpf_neg(v) return mpf_pos(v, prec, rnd or round_fast)
def mpf_bernoulli_huge(n, prec, rnd=None): wp = prec + 10 piprec = wp + int(math.log(n,2)) v = mpf_gamma_int(n+1, wp) v = mpf_mul(v, mpf_zeta_int(n, wp), wp) v = mpf_mul(v, mpf_pow_int(mpf_pi(piprec), -n, wp)) v = mpf_shift(v, 1-n) if not n & 3: v = mpf_neg(v) return mpf_pos(v, prec, rnd or round_fast)
def mpc_gamma(x, prec, rounding=round_fast, p1=1): re, im = x if im == fzero: return mpf_gamma(re, prec, rounding, p1), fzero # More precision is needed for enormous x. sign, man, exp, bc = re isign, iman, iexp, ibc = im if re == fzero: size = iexp + ibc else: size = max(exp + bc, iexp + ibc) if size > 5: size = int(size * math.log(size, 2)) reflect = sign or (exp + bc < -1) wp = prec + max(0, size) + 25 # Near x = 0 pole (TODO: other poles) if p1: if size < -prec - 5: return mpc_add_mpf(mpc_div(mpc_one, x, 2*prec+10), \ mpf_neg(mpf_euler(2*prec+10)), prec, rounding) elif size < -5: wp += (-2 * size) if p1: # Should be done exactly! re_orig = re re = mpf_sub(re, fone, bc + abs(exp) + 2) x = re, im if reflect: # Reflection formula wp += 15 pi = mpf_pi(wp), fzero pix = mpc_mul(x, pi, wp) t = mpc_sin_pi(x, wp) u = mpc_sub(mpc_one, x, wp) g = mpc_gamma(u, wp) w = mpc_mul(t, g, wp) return mpc_div(pix, w, wp) # Extremely close to the real line? # XXX: reflection formula if iexp + ibc < -wp: a = mpf_gamma(re_orig, wp) b = mpf_psi0(re_orig, wp) gamma_diff = mpf_div(a, b, wp) return mpf_pos(a, prec, rounding), mpf_mul(gamma_diff, im, prec, rounding) sprec, a, c = get_spouge_coefficients(wp) s = spouge_sum_complex(re, im, sprec, a, c) # gamma = exp(log(x+a)*(x+0.5) - xpa) * s repa = mpf_add(re, from_int(a), wp) logxpa = mpc_log((repa, im), wp) reph = mpf_add(re, fhalf, wp) t = mpc_sub(mpc_mul(logxpa, (reph, im), wp), (repa, im), wp) t = mpc_mul(mpc_exp(t, wp), s, prec, rounding) return t
def mpf_zeta_int(s, prec, rnd=round_fast): """ Optimized computation of zeta(s) for an integer s. """ wp = prec + 20 s = int(s) if s in zeta_int_cache and zeta_int_cache[s][0] >= wp: return mpf_pos(zeta_int_cache[s][1], prec, rnd) if s < 2: if s == 1: raise ValueError("zeta(1) pole") if not s: return mpf_neg(fhalf) return mpf_div(mpf_bernoulli(-s + 1, wp), from_int(s - 1), prec, rnd) # 2^-s term vanishes? if s >= wp: return mpf_perturb(fone, 0, prec, rnd) # 5^-s term vanishes? elif s >= wp * 0.431: t = one = 1 << wp t += 1 << (wp - s) t += one // (MPZ_THREE**s) t += 1 << max(0, wp - s * 2) return from_man_exp(t, -wp, prec, rnd) else: # Fast enough to sum directly? # Even better, we use the Euler product (idea stolen from pari) m = (float(wp) / (s - 1) + 1) if m < 30: needed_terms = int(2.0**m + 1) if needed_terms < int(wp / 2.54 + 5) / 10: t = fone for k in list_primes(needed_terms): #print k, needed_terms powprec = int(wp - s * math.log(k, 2)) if powprec < 2: break a = mpf_sub(fone, mpf_pow_int(from_int(k), -s, powprec), wp) t = mpf_mul(t, a, wp) return mpf_div(fone, t, wp) # Use Borwein's algorithm n = int(wp / 2.54 + 5) d = borwein_coefficients(n) t = MPZ_ZERO s = MPZ(s) for k in xrange(n): t += (((-1)**k * (d[k] - d[n])) << wp) // (k + 1)**s t = (t << wp) // (-d[n]) t = (t << wp) // ((1 << wp) - (1 << (wp + 1 - s))) if (s in zeta_int_cache and zeta_int_cache[s][0] < wp) or (s not in zeta_int_cache): zeta_int_cache[s] = (wp, from_man_exp(t, -wp - wp)) return from_man_exp(t, -wp - wp, prec, rnd)
def mpi_abs(s, prec): sa, sb = s sas = mpf_sign(sa) sbs = mpf_sign(sb) # Both points nonnegative? if sas >= 0: a = mpf_pos(sa, prec, round_floor) b = mpf_pos(sb, prec, round_ceiling) # Upper point nonnegative? elif sbs >= 0: a = fzero negsa = mpf_neg(sa) if mpf_lt(negsa, sb): b = mpf_pos(sb, prec, round_ceiling) else: b = mpf_pos(negsa, prec, round_ceiling) # Both negative? else: a = mpf_neg(sb, prec, round_floor) b = mpf_neg(sa, prec, round_ceiling) return a, b
def mpc_gamma(x, prec, rounding=round_fast, p1=1): re, im = x if im == fzero: return mpf_gamma(re, prec, rounding, p1), fzero # More precision is needed for enormous x. sign, man, exp, bc = re isign, iman, iexp, ibc = im if re == fzero: size = iexp+ibc else: size = max(exp+bc, iexp+ibc) if size > 5: size = int(size * math.log(size,2)) reflect = sign or (exp+bc < -1) wp = prec + max(0, size) + 25 # Near x = 0 pole (TODO: other poles) if p1: if size < -prec-5: return mpc_add_mpf(mpc_div(mpc_one, x, 2*prec+10), \ mpf_neg(mpf_euler(2*prec+10)), prec, rounding) elif size < -5: wp += (-2*size) if p1: # Should be done exactly! re_orig = re re = mpf_sub(re, fone, bc+abs(exp)+2) x = re, im if reflect: # Reflection formula wp += 15 pi = mpf_pi(wp), fzero pix = mpc_mul(x, pi, wp) t = mpc_sin_pi(x, wp) u = mpc_sub(mpc_one, x, wp) g = mpc_gamma(u, wp) w = mpc_mul(t, g, wp) return mpc_div(pix, w, wp) # Extremely close to the real line? # XXX: reflection formula if iexp+ibc < -wp: a = mpf_gamma(re_orig, wp) b = mpf_psi0(re_orig, wp) gamma_diff = mpf_div(a, b, wp) return mpf_pos(a, prec, rounding), mpf_mul(gamma_diff, im, prec, rounding) sprec, a, c = get_spouge_coefficients(wp) s = spouge_sum_complex(re, im, sprec, a, c) # gamma = exp(log(x+a)*(x+0.5) - xpa) * s repa = mpf_add(re, from_int(a), wp) logxpa = mpc_log((repa, im), wp) reph = mpf_add(re, fhalf, wp) t = mpc_sub(mpc_mul(logxpa, (reph, im), wp), (repa, im), wp) t = mpc_mul(mpc_exp(t, wp), s, prec, rounding) return t
def mpf_zeta_int(s, prec, rnd=round_fast): """ Optimized computation of zeta(s) for an integer s. """ wp = prec + 20 s = int(s) if s in zeta_int_cache and zeta_int_cache[s][0] >= wp: return mpf_pos(zeta_int_cache[s][1], prec, rnd) if s < 2: if s == 1: raise ValueError("zeta(1) pole") if not s: return mpf_neg(fhalf) return mpf_div(mpf_bernoulli(-s+1, wp), from_int(s-1), prec, rnd) # 2^-s term vanishes? if s >= wp: return mpf_perturb(fone, 0, prec, rnd) # 5^-s term vanishes? elif s >= wp*0.431: t = one = 1 << wp t += 1 << (wp - s) t += one // (MPZ_THREE ** s) t += 1 << max(0, wp - s*2) return from_man_exp(t, -wp, prec, rnd) else: # Fast enough to sum directly? # Even better, we use the Euler product (idea stolen from pari) m = (float(wp)/(s-1) + 1) if m < 30: needed_terms = int(2.0**m + 1) if needed_terms < int(wp/2.54 + 5) / 10: t = fone for k in list_primes(needed_terms): #print k, needed_terms powprec = int(wp - s*math.log(k,2)) if powprec < 2: break a = mpf_sub(fone, mpf_pow_int(from_int(k), -s, powprec), wp) t = mpf_mul(t, a, wp) return mpf_div(fone, t, wp) # Use Borwein's algorithm n = int(wp/2.54 + 5) d = borwein_coefficients(n) t = MPZ_ZERO s = MPZ(s) for k in xrange(n): t += (((-1)**k * (d[k] - d[n])) << wp) // (k+1)**s t = (t << wp) // (-d[n]) t = (t << wp) // ((1 << wp) - (1 << (wp+1-s))) if (s in zeta_int_cache and zeta_int_cache[s][0] < wp) or (s not in zeta_int_cache): zeta_int_cache[s] = (wp, from_man_exp(t, -wp-wp)) return from_man_exp(t, -wp-wp, prec, rnd)
def twinprime_fixed(prec): def I(n): return sum(moebius(d)<<(n//d) for d in xrange(1,n+1) if not n%d)//n wp = 2*prec + 30 res = fone primes = [from_rational(1,p,wp) for p in [2,3,5,7]] ppowers = [mpf_mul(p,p,wp) for p in primes] n = 2 while 1: a = mpf_zeta_int(n, wp) for i in range(4): a = mpf_mul(a, mpf_sub(fone, ppowers[i]), wp) ppowers[i] = mpf_mul(ppowers[i], primes[i], wp) a = mpf_pow_int(a, -I(n), wp) if mpf_pos(a, prec+10, 'n') == fone: break #from libmpf import to_str #print n, to_str(mpf_sub(fone, a), 6) res = mpf_mul(res, a, wp) n += 1 res = mpf_mul(res, from_int(3*15*35), wp) res = mpf_div(res, from_int(4*16*36), wp) return to_fixed(res, prec)
def __new__(cls, val=fzero, **kwargs): """A new mpf can be created from a Python float, an int, a or a decimal string representing a number in floating-point format.""" prec, rounding = prec_rounding if kwargs: prec = kwargs.get('prec', prec) if 'dps' in kwargs: prec = dps_to_prec(kwargs['dps']) rounding = kwargs.get('rounding', rounding) if type(val) is cls: sign, man, exp, bc = val._mpf_ if (not man) and exp: return val return make_mpf(normalize(sign, man, exp, bc, prec, rounding)) elif type(val) is tuple: if len(val) == 2: return make_mpf(from_man_exp(val[0], val[1], prec, rounding)) if len(val) == 4: sign, man, exp, bc = val return make_mpf(normalize(sign, MP_BASE(man), exp, bc, prec, rounding)) raise ValueError else: return make_mpf(mpf_pos(mpf_convert_arg(val, prec, rounding), prec, rounding))
def mpc_ei(z, prec, rnd=round_fast, e1=False): if e1: z = mpc_neg(z) a, b = z asign, aman, aexp, abc = a bsign, bman, bexp, bbc = b if b == fzero: if e1: x = mpf_neg(mpf_ei(a, prec, rnd)) if not asign: y = mpf_neg(mpf_pi(prec, rnd)) else: y = fzero return x, y else: return mpf_ei(a, prec, rnd), fzero if a != fzero: if not aman or not bman: return (fnan, fnan) wp = prec + 40 amag = aexp + abc bmag = bexp + bbc zmag = max(amag, bmag) can_use_asymp = zmag > wp if not can_use_asymp: zabsint = abs(to_int(a)) + abs(to_int(b)) can_use_asymp = zabsint > int(wp * 0.693) + 20 try: if can_use_asymp: if zmag > wp: v = fone, fzero else: zre = to_fixed(a, wp) zim = to_fixed(b, wp) vre, vim = complex_ei_asymptotic(zre, zim, wp) v = from_man_exp(vre, -wp), from_man_exp(vim, -wp) v = mpc_mul(v, mpc_exp(z, wp), wp) v = mpc_div(v, z, wp) if e1: v = mpc_neg(v, prec, rnd) else: x, y = v if bsign: v = mpf_pos(x, prec, rnd), mpf_sub(y, mpf_pi(wp), prec, rnd) else: v = mpf_pos(x, prec, rnd), mpf_add(y, mpf_pi(wp), prec, rnd) return v except NoConvergence: pass #wp += 2*max(0,zmag) wp += 2 * int(to_int(mpc_abs(z, 5))) zre = to_fixed(a, wp) zim = to_fixed(b, wp) vre, vim = complex_ei_taylor(zre, zim, wp) vre += euler_fixed(wp) v = from_man_exp(vre, -wp), from_man_exp(vim, -wp) if e1: u = mpc_log(mpc_neg(z), wp) else: u = mpc_log(z, wp) v = mpc_add(v, u, prec, rnd) if e1: v = mpc_neg(v) return v
def mpc_pos(z, prec, rnd=round_fast): a, b = z return mpf_pos(a, prec, rnd), mpf_pos(b, prec, rnd)
def mpf_bernoulli(n, prec, rnd=None): """Computation of Bernoulli numbers (numerically)""" if n < 2: if n < 0: raise ValueError("Bernoulli numbers only defined for n >= 0") if n == 0: return fone if n == 1: return mpf_neg(fhalf) # For odd n > 1, the Bernoulli numbers are zero if n & 1: return fzero # If precision is extremely high, we can save time by computing # the Bernoulli number at a lower precision that is sufficient to # obtain the exact fraction, round to the exact fraction, and # convert the fraction back to an mpf value at the original precision if prec > BERNOULLI_PREC_CUTOFF and prec > bernoulli_size(n)*1.1 + 1000: p, q = bernfrac(n) return from_rational(p, q, prec, rnd or round_floor) if n > MAX_BERNOULLI_CACHE: return mpf_bernoulli_huge(n, prec, rnd) wp = prec + 30 # Reuse nearby precisions wp += 32 - (prec & 31) cached = bernoulli_cache.get(wp) if cached: numbers, state = cached if n in numbers: if not rnd: return numbers[n] return mpf_pos(numbers[n], prec, rnd) m, bin, bin1 = state if n - m > 10: return mpf_bernoulli_huge(n, prec, rnd) else: if n > 10: return mpf_bernoulli_huge(n, prec, rnd) numbers = {0:fone} m, bin, bin1 = state = [2, MPZ(10), MPZ_ONE] bernoulli_cache[wp] = (numbers, state) while m <= n: #print m case = m % 6 # Accurately estimate size of B_m so we can use # fixed point math without using too much precision szbm = bernoulli_size(m) s = 0 sexp = max(0, szbm) - wp if m < 6: a = MPZ_ZERO else: a = bin1 for j in xrange(1, m//6+1): usign, uman, uexp, ubc = u = numbers[m-6*j] if usign: uman = -uman s += lshift(a*uman, uexp-sexp) # Update inner binomial coefficient j6 = 6*j a *= ((m-5-j6)*(m-4-j6)*(m-3-j6)*(m-2-j6)*(m-1-j6)*(m-j6)) a //= ((4+j6)*(5+j6)*(6+j6)*(7+j6)*(8+j6)*(9+j6)) if case == 0: b = mpf_rdiv_int(m+3, f3, wp) if case == 2: b = mpf_rdiv_int(m+3, f3, wp) if case == 4: b = mpf_rdiv_int(-m-3, f6, wp) s = from_man_exp(s, sexp, wp) b = mpf_div(mpf_sub(b, s, wp), from_int(bin), wp) numbers[m] = b m += 2 # Update outer binomial coefficient bin = bin * ((m+2)*(m+3)) // (m*(m-1)) if m > 6: bin1 = bin1 * ((2+m)*(3+m)) // ((m-7)*(m-6)) state[:] = [m, bin, bin1] return numbers[n]
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)
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 mpc_ei(z, prec, rnd=round_fast, e1=False): if e1: z = mpc_neg(z) a, b = z asign, aman, aexp, abc = a bsign, bman, bexp, bbc = b if b == fzero: if e1: x = mpf_neg(mpf_ei(a, prec, rnd)) if not asign: y = mpf_neg(mpf_pi(prec, rnd)) else: y = fzero return x, y else: return mpf_ei(a, prec, rnd), fzero if a != fzero: if not aman or not bman: return (fnan, fnan) wp = prec + 40 amag = aexp+abc bmag = bexp+bbc zmag = max(amag, bmag) can_use_asymp = zmag > wp if not can_use_asymp: zabsint = abs(to_int(a)) + abs(to_int(b)) can_use_asymp = zabsint > int(wp*0.693) + 20 try: if can_use_asymp: if zmag > wp: v = fone, fzero else: zre = to_fixed(a, wp) zim = to_fixed(b, wp) vre, vim = complex_ei_asymptotic(zre, zim, wp) v = from_man_exp(vre, -wp), from_man_exp(vim, -wp) v = mpc_mul(v, mpc_exp(z, wp), wp) v = mpc_div(v, z, wp) if e1: v = mpc_neg(v, prec, rnd) else: x, y = v if bsign: v = mpf_pos(x, prec, rnd), mpf_sub(y, mpf_pi(wp), prec, rnd) else: v = mpf_pos(x, prec, rnd), mpf_add(y, mpf_pi(wp), prec, rnd) return v except NoConvergence: pass #wp += 2*max(0,zmag) wp += 2*int(to_int(mpc_abs(z, 5))) zre = to_fixed(a, wp) zim = to_fixed(b, wp) vre, vim = complex_ei_taylor(zre, zim, wp) vre += euler_fixed(wp) v = from_man_exp(vre,-wp), from_man_exp(vim,-wp) if e1: u = mpc_log(mpc_neg(z),wp) else: u = mpc_log(z,wp) v = mpc_add(v, u, prec, rnd) if e1: v = mpc_neg(v) return v
def mpf_nthroot(s, n, prec, rnd=round_fast): """nth-root of a positive number Use the Newton method when faster, otherwise use x**(1/n) """ sign, man, exp, bc = s if sign: raise ComplexResult("nth root of a negative number") if not man: if s == fnan: return fnan if s == fzero: if n > 0: return fzero if n == 0: return fone return finf # Infinity if not n: return fnan if n < 0: return fzero return finf flag_inverse = False if n < 2: if n == 0: return fone if n == 1: return mpf_pos(s, prec, rnd) if n == -1: return mpf_div(fone, s, prec, rnd) # n < 0 rnd = reciprocal_rnd[rnd] flag_inverse = True extra_inverse = 5 prec += extra_inverse n = -n if n > 20 and (n >= 20000 or prec < int(233 + 28.3 * n**0.62)): prec2 = prec + 10 fn = from_int(n) nth = mpf_rdiv_int(1, fn, prec2) r = mpf_pow(s, nth, prec2, rnd) s = normalize(r[0], r[1], r[2], r[3], prec, rnd) if flag_inverse: return mpf_div(fone, s, prec-extra_inverse, rnd) else: return s # Convert to a fixed-point number with prec2 bits. prec2 = prec + 2*n - (prec%n) # a few tests indicate that # for 10 < n < 10**4 a bit more precision is needed if n > 10: prec2 += prec2//10 prec2 = prec2 - prec2%n # Mantissa may have more bits than we need. Trim it down. shift = bc - prec2 # Adjust exponents to make prec2 and exp+shift multiples of n. sign1 = 0 es = exp+shift if es < 0: sign1 = 1 es = -es if sign1: shift += es%n else: shift -= es%n man = rshift(man, shift) extra = 10 exp1 = ((exp+shift-(n-1)*prec2)//n) - extra rnd_shift = 0 if flag_inverse: if rnd == 'u' or rnd == 'c': rnd_shift = 1 else: if rnd == 'd' or rnd == 'f': rnd_shift = 1 man = nthroot_fixed(man+rnd_shift, n, prec2, exp1) s = from_man_exp(man, exp1, prec, rnd) if flag_inverse: return mpf_div(fone, s, prec-extra_inverse, rnd) else: return s
def mpi_pos(s, prec): sa, sb = s a = mpf_pos(sa, prec, round_floor) b = mpf_pos(sb, prec, round_ceiling) return a, b
def mpf_bernoulli(n, prec, rnd=None): """Computation of Bernoulli numbers (numerically)""" if n < 2: if n < 0: raise ValueError("Bernoulli numbers only defined for n >= 0") if n == 0: return fone if n == 1: return mpf_neg(fhalf) # For odd n > 1, the Bernoulli numbers are zero if n & 1: return fzero # If precision is extremely high, we can save time by computing # the Bernoulli number at a lower precision that is sufficient to # obtain the exact fraction, round to the exact fraction, and # convert the fraction back to an mpf value at the original precision if prec > BERNOULLI_PREC_CUTOFF and prec > bernoulli_size(n) * 1.1 + 1000: p, q = bernfrac(n) return from_rational(p, q, prec, rnd or round_floor) if n > MAX_BERNOULLI_CACHE: return mpf_bernoulli_huge(n, prec, rnd) wp = prec + 30 # Reuse nearby precisions wp += 32 - (prec & 31) cached = bernoulli_cache.get(wp) if cached: numbers, state = cached if n in numbers: if not rnd: return numbers[n] return mpf_pos(numbers[n], prec, rnd) m, bin, bin1 = state if n - m > 10: return mpf_bernoulli_huge(n, prec, rnd) else: if n > 10: return mpf_bernoulli_huge(n, prec, rnd) numbers = {0: fone} m, bin, bin1 = state = [2, MP_BASE(10), MP_ONE] bernoulli_cache[wp] = (numbers, state) while m <= n: #print m case = m % 6 # Accurately estimate size of B_m so we can use # fixed point math without using too much precision szbm = bernoulli_size(m) s = 0 sexp = max(0, szbm) - wp if m < 6: a = MP_ZERO else: a = bin1 for j in xrange(1, m // 6 + 1): usign, uman, uexp, ubc = u = numbers[m - 6 * j] if usign: uman = -uman s += lshift(a * uman, uexp - sexp) # Update inner binomial coefficient j6 = 6 * j a *= ((m - 5 - j6) * (m - 4 - j6) * (m - 3 - j6) * (m - 2 - j6) * (m - 1 - j6) * (m - j6)) a //= ((4 + j6) * (5 + j6) * (6 + j6) * (7 + j6) * (8 + j6) * (9 + j6)) if case == 0: b = mpf_rdiv_int(m + 3, f3, wp) if case == 2: b = mpf_rdiv_int(m + 3, f3, wp) if case == 4: b = mpf_rdiv_int(-m - 3, f6, wp) s = from_man_exp(s, sexp, wp) b = mpf_div(mpf_sub(b, s, wp), from_int(bin), wp) numbers[m] = b m += 2 # Update outer binomial coefficient bin = bin * ((m + 2) * (m + 3)) // (m * (m - 1)) if m > 6: bin1 = bin1 * ((2 + m) * (3 + m)) // ((m - 7) * (m - 6)) state[:] = [m, bin, bin1]
def mpi_mul(s, t, prec): sa, sb = s ta, tb = t sas = mpf_sign(sa) sbs = mpf_sign(sb) tas = mpf_sign(ta) tbs = mpf_sign(tb) if sas == sbs == 0: # Should maybe be undefined if ta == fninf or tb == finf: return fninf, finf return fzero, fzero if tas == tbs == 0: # Should maybe be undefined if sa == fninf or sb == finf: return fninf, finf return fzero, fzero if sas >= 0: # positive * positive if tas >= 0: a = mpf_mul(sa, ta, prec, round_floor) b = mpf_mul(sb, tb, prec, round_ceiling) if a == fnan: a = fzero if b == fnan: b = finf # positive * negative elif tbs <= 0: a = mpf_mul(sb, ta, prec, round_floor) b = mpf_mul(sa, tb, prec, round_ceiling) if a == fnan: a = fninf if b == fnan: b = fzero # positive * both signs else: a = mpf_mul(sb, ta, prec, round_floor) b = mpf_mul(sb, tb, prec, round_ceiling) if a == fnan: a = fninf if b == fnan: b = finf elif sbs <= 0: # negative * positive if tas >= 0: a = mpf_mul(sa, tb, prec, round_floor) b = mpf_mul(sb, ta, prec, round_ceiling) if a == fnan: a = fninf if b == fnan: b = fzero # negative * negative elif tbs <= 0: a = mpf_mul(sb, tb, prec, round_floor) b = mpf_mul(sa, ta, prec, round_ceiling) if a == fnan: a = fzero if b == fnan: b = finf # negative * both signs else: a = mpf_mul(sb, tb, prec, round_floor) b = mpf_mul(sa, ta, prec, round_ceiling) if a == fnan: a = fninf if b == fnan: b = finf else: # General case: perform all cross-multiplications and compare # Since the multiplications can be done exactly, we need only # do 4 (instead of 8: two for each rounding mode) cases = [mpf_mul(sa, ta), mpf_mul(sa, tb), mpf_mul(sb, ta), mpf_mul(sb, tb)] if fnan in cases: a, b = (fninf, finf) else: cases = sorted(cases, cmp=mpf_cmp) a = mpf_pos(cases[0], prec, round_floor) b = mpf_pos(cases[-1], prec, round_ceiling) return a, b
return rs + " + " + to_str(im, dps) + "j" def mpc_add((a, b), (c, d), prec, rnd=round_fast): return mpf_add(a, c, prec, rnd), mpf_add(b, d, prec, rnd) def mpc_add_mpf((a, b), p, prec, rnd=round_fast): return mpf_add(a, p, prec, rnd), b def mpc_sub((a, b), (c, d), prec, rnd=round_fast): return mpf_sub(a, c, prec, rnd), mpf_sub(b, d, prec, rnd) def mpc_sub_mpf((a, b), p, prec, rnd=round_fast): return mpf_sub(a, p, prec, rnd), b def mpc_pos((a, b), prec, rnd=round_fast): return mpf_pos(a, prec, rnd), mpf_pos(b, prec, rnd) def mpc_neg((a, b), prec=None, rnd=round_fast): return mpf_neg(a, prec, rnd), mpf_neg(b, prec, rnd) def mpc_shift((a, b), n): return mpf_shift(a, n), mpf_shift(b, n) def mpc_abs((a, b), prec, rnd=round_fast): """Absolute value of a complex number, |a+bi|. Returns an mpf value.""" return mpf_hypot(a, b, prec, rnd) def mpc_arg((a, b), prec, rnd=round_fast): """Argument of a complex number. Returns an mpf value.""" return mpf_atan2(b, a, prec, rnd)
def mpc_add_mpf((a, b), p, prec, rnd=round_fast): return mpf_add(a, p, prec, rnd), b def mpc_sub((a, b), (c, d), prec, rnd=round_fast): return mpf_sub(a, c, prec, rnd), mpf_sub(b, d, prec, rnd) def mpc_sub_mpf((a, b), p, prec, rnd=round_fast): return mpf_sub(a, p, prec, rnd), b def mpc_pos((a, b), prec, rnd=round_fast): return mpf_pos(a, prec, rnd), mpf_pos(b, prec, rnd) def mpc_neg((a, b), prec=None, rnd=round_fast): return mpf_neg(a, prec, rnd), mpf_neg(b, prec, rnd) def mpc_shift((a, b), n): return mpf_shift(a, n), mpf_shift(b, n) def mpc_abs((a, b), prec, rnd=round_fast): """Absolute value of a complex number, |a+bi|. Returns an mpf value.""" return mpf_hypot(a, b, prec, rnd)
def __pos__(s): return make_mpf(mpf_pos(s._mpf_, *prec_rounding)) def __neg__(s): return make_mpf(mpf_neg(s._mpf_, *prec_rounding))
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 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 mpi_mul(s, t, prec): sa, sb = s ta, tb = t sas = mpf_sign(sa) sbs = mpf_sign(sb) tas = mpf_sign(ta) tbs = mpf_sign(tb) if sas == sbs == 0: # Should maybe be undefined if ta == fninf or tb == finf: return fninf, finf return fzero, fzero if tas == tbs == 0: # Should maybe be undefined if sa == fninf or sb == finf: return fninf, finf return fzero, fzero if sas >= 0: # positive * positive if tas >= 0: a = mpf_mul(sa, ta, prec, round_floor) b = mpf_mul(sb, tb, prec, round_ceiling) if a == fnan: a = fzero if b == fnan: b = finf # positive * negative elif tbs <= 0: a = mpf_mul(sb, ta, prec, round_floor) b = mpf_mul(sa, tb, prec, round_ceiling) if a == fnan: a = fninf if b == fnan: b = fzero # positive * both signs else: a = mpf_mul(sb, ta, prec, round_floor) b = mpf_mul(sb, tb, prec, round_ceiling) if a == fnan: a = fninf if b == fnan: b = finf elif sbs <= 0: # negative * positive if tas >= 0: a = mpf_mul(sa, tb, prec, round_floor) b = mpf_mul(sb, ta, prec, round_ceiling) if a == fnan: a = fninf if b == fnan: b = fzero # negative * negative elif tbs <= 0: a = mpf_mul(sb, tb, prec, round_floor) b = mpf_mul(sa, ta, prec, round_ceiling) if a == fnan: a = fzero if b == fnan: b = finf # negative * both signs else: a = mpf_mul(sa, tb, prec, round_floor) b = mpf_mul(sa, ta, prec, round_ceiling) if a == fnan: a = fninf if b == fnan: b = finf else: # General case: perform all cross-multiplications and compare # Since the multiplications can be done exactly, we need only # do 4 (instead of 8: two for each rounding mode) cases = [mpf_mul(sa, ta), mpf_mul(sa, tb), mpf_mul(sb, ta), mpf_mul(sb, tb)] if fnan in cases: a, b = (fninf, finf) else: cases = sorted(cases, cmp=mpf_cmp) a = mpf_pos(cases[0], prec, round_floor) b = mpf_pos(cases[-1], prec, round_ceiling) return a, b