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from .functions import defun, defun_wrapped
@defun_wrapped
def _erf_complex(ctx, z):
z2 = ctx.square_exp_arg(z, -1)
#z2 = -z**2
v = (2/ctx.sqrt(ctx.pi))*z * ctx.hyp1f1((1,2),(3,2), z2)
if not ctx._re(z):
v = ctx._im(v)*ctx.j
return v
@defun_wrapped
def _erfc_complex(ctx, z):
if ctx.re(z) > 2:
z2 = ctx.square_exp_arg(z)
nz2 = ctx.fneg(z2, exact=True)
v = ctx.exp(nz2)/ctx.sqrt(ctx.pi) * ctx.hyperu((1,2),(1,2), z2)
else:
v = 1 - ctx._erf_complex(z)
if not ctx._re(z):
v = 1+ctx._im(v)*ctx.j
return v
@defun
def erf(ctx, z):
z = ctx.convert(z)
if ctx._is_real_type(z):
try:
return ctx._erf(z)
except NotImplementedError:
pass
if ctx._is_complex_type(z) and not z.imag:
try:
return type(z)(ctx._erf(z.real))
except NotImplementedError:
pass
return ctx._erf_complex(z)
@defun
def erfc(ctx, z):
z = ctx.convert(z)
if ctx._is_real_type(z):
try:
return ctx._erfc(z)
except NotImplementedError:
pass
if ctx._is_complex_type(z) and not z.imag:
try:
return type(z)(ctx._erfc(z.real))
except NotImplementedError:
pass
return ctx._erfc_complex(z)
@defun
def square_exp_arg(ctx, z, mult=1, reciprocal=False):
prec = ctx.prec*4+20
if reciprocal:
z2 = ctx.fmul(z, z, prec=prec)
z2 = ctx.fdiv(ctx.one, z2, prec=prec)
else:
z2 = ctx.fmul(z, z, prec=prec)
if mult != 1:
z2 = ctx.fmul(z2, mult, exact=True)
return z2
@defun_wrapped
def erfi(ctx, z):
if not z:
return z
z2 = ctx.square_exp_arg(z)
v = (2/ctx.sqrt(ctx.pi)*z) * ctx.hyp1f1((1,2), (3,2), z2)
if not ctx._re(z):
v = ctx._im(v)*ctx.j
return v
@defun_wrapped
def erfinv(ctx, x):
xre = ctx._re(x)
if (xre != x) or (xre < -1) or (xre > 1):
return ctx.bad_domain("erfinv(x) is defined only for -1 <= x <= 1")
x = xre
#if ctx.isnan(x): return x
if not x: return x
if x == 1: return ctx.inf
if x == -1: return ctx.ninf
if abs(x) < 0.9:
a = 0.53728*x**3 + 0.813198*x
else:
# An asymptotic formula
u = ctx.ln(2/ctx.pi/(abs(x)-1)**2)
a = ctx.sign(x) * ctx.sqrt(u - ctx.ln(u))/ctx.sqrt(2)
ctx.prec += 10
return ctx.findroot(lambda t: ctx.erf(t)-x, a)
@defun_wrapped
def npdf(ctx, x, mu=0, sigma=1):
sigma = ctx.convert(sigma)
return ctx.exp(-(x-mu)**2/(2*sigma**2)) / (sigma*ctx.sqrt(2*ctx.pi))
@defun_wrapped
def ncdf(ctx, x, mu=0, sigma=1):
a = (x-mu)/(sigma*ctx.sqrt(2))
if a < 0:
return ctx.erfc(-a)/2
else:
return (1+ctx.erf(a))/2
@defun_wrapped
def betainc(ctx, a, b, x1=0, x2=1, regularized=False):
if x1 == x2:
v = 0
elif not x1:
if x1 == 0 and x2 == 1:
v = ctx.beta(a, b)
else:
v = x2**a * ctx.hyp2f1(a, 1-b, a+1, x2) / a
else:
m, d = ctx.nint_distance(a)
if m <= 0:
if d < -ctx.prec:
h = +ctx.eps
ctx.prec *= 2
a += h
elif d < -4:
ctx.prec -= d
s1 = x2**a * ctx.hyp2f1(a,1-b,a+1,x2)
s2 = x1**a * ctx.hyp2f1(a,1-b,a+1,x1)
v = (s1 - s2) / a
if regularized:
v /= ctx.beta(a,b)
return v
@defun
def gammainc(ctx, z, a=0, b=None, regularized=False):
regularized = bool(regularized)
z = ctx.convert(z)
if a is None:
a = ctx.zero
lower_modified = False
else:
a = ctx.convert(a)
lower_modified = a != ctx.zero
if b is None:
b = ctx.inf
upper_modified = False
else:
b = ctx.convert(b)
upper_modified = b != ctx.inf
# Complete gamma function
if not (upper_modified or lower_modified):
if regularized:
if ctx.re(z) < 0:
return ctx.inf
elif ctx.re(z) > 0:
return ctx.one
else:
return ctx.nan
return ctx.gamma(z)
if a == b:
return ctx.zero
# Standardize
if ctx.re(a) > ctx.re(b):
return -ctx.gammainc(z, b, a, regularized)
# Generalized gamma
if upper_modified and lower_modified:
return +ctx._gamma3(z, a, b, regularized)
# Upper gamma
elif lower_modified:
return ctx._upper_gamma(z, a, regularized)
# Lower gamma
elif upper_modified:
return ctx._lower_gamma(z, b, regularized)
@defun
def _lower_gamma(ctx, z, b, regularized=False):
# Pole
if ctx.isnpint(z):
return type(z)(ctx.inf)
G = [z] * regularized
negb = ctx.fneg(b, exact=True)
def h(z):
T1 = [ctx.exp(negb), b, z], [1, z, -1], [], G, [1], [1+z], b
return (T1,)
return ctx.hypercomb(h, [z])
@defun
def _upper_gamma(ctx, z, a, regularized=False):
# Fast integer case, when available
if ctx.isint(z):
try:
if regularized:
# Gamma pole
if ctx.isnpint(z):
return type(z)(ctx.zero)
orig = ctx.prec
try:
ctx.prec += 10
return ctx._gamma_upper_int(z, a) / ctx.gamma(z)
finally:
ctx.prec = orig
else:
return ctx._gamma_upper_int(z, a)
except NotImplementedError:
pass
# hypercomb is unable to detect the exact zeros, so handle them here
if z == 2 and a == -1:
return (z+a)*0
if z == 3 and (a == -1-1j or a == -1+1j):
return (z+a)*0
nega = ctx.fneg(a, exact=True)
G = [z] * regularized
# Use 2F0 series when possible; fall back to lower gamma representation
try:
def h(z):
r = z-1
return [([ctx.exp(nega), a], [1, r], [], G, [1, -r], [], 1/nega)]
return ctx.hypercomb(h, [z], force_series=True)
except ctx.NoConvergence:
def h(z):
T1 = [], [1, z-1], [z], G, [], [], 0
T2 = [-ctx.exp(nega), a, z], [1, z, -1], [], G, [1], [1+z], a
return T1, T2
return ctx.hypercomb(h, [z])
@defun
def _gamma3(ctx, z, a, b, regularized=False):
pole = ctx.isnpint(z)
if regularized and pole:
return ctx.zero
try:
ctx.prec += 15
# We don't know in advance whether it's better to write as a difference
# of lower or upper gamma functions, so try both
T1 = ctx.gammainc(z, a, regularized=regularized)
T2 = ctx.gammainc(z, b, regularized=regularized)
R = T1 - T2
if ctx.mag(R) - max(ctx.mag(T1), ctx.mag(T2)) > -10:
return R
if not pole:
T1 = ctx.gammainc(z, 0, b, regularized=regularized)
T2 = ctx.gammainc(z, 0, a, regularized=regularized)
R = T1 - T2
# May be ok, but should probably at least print a warning
# about possible cancellation
if 1: #ctx.mag(R) - max(ctx.mag(T1), ctx.mag(T2)) > -10:
return R
finally:
ctx.prec -= 15
raise NotImplementedError
@defun_wrapped
def expint(ctx, n, z):
if ctx.isint(n) and ctx._is_real_type(z):
try:
return ctx._expint_int(n, z)
except NotImplementedError:
pass
if ctx.isnan(n) or ctx.isnan(z):
return z*n
if z == ctx.inf:
return 1/z
if z == 0:
# integral from 1 to infinity of t^n
if ctx.re(n) <= 1:
# TODO: reasonable sign of infinity
return type(z)(ctx.inf)
else:
return ctx.one/(n-1)
if n == 0:
return ctx.exp(-z)/z
if n == -1:
return ctx.exp(-z)*(z+1)/z**2
return z**(n-1) * ctx.gammainc(1-n, z)
@defun_wrapped
def li(ctx, z, offset=False):
if offset:
if z == 2:
return ctx.zero
return ctx.ei(ctx.ln(z)) - ctx.ei(ctx.ln2)
if not z:
return z
if z == 1:
return ctx.ninf
return ctx.ei(ctx.ln(z))
@defun
def ei(ctx, z):
try:
return ctx._ei(z)
except NotImplementedError:
return ctx._ei_generic(z)
@defun_wrapped
def _ei_generic(ctx, z):
# Note: the following is currently untested because mp and fp
# both use special-case ei code
if z == ctx.inf:
return z
if z == ctx.ninf:
return ctx.zero
if ctx.mag(z) > 1:
try:
r = ctx.one/z
v = ctx.exp(z)*ctx.hyper([1,1],[],r,
maxterms=ctx.prec, force_series=True)/z
im = ctx._im(z)
if im > 0:
v += ctx.pi*ctx.j
if im < 0:
v -= ctx.pi*ctx.j
return v
except ctx.NoConvergence:
pass
v = z*ctx.hyp2f2(1,1,2,2,z) + ctx.euler
if ctx._im(z):
v += 0.5*(ctx.log(z) - ctx.log(ctx.one/z))
else:
v += ctx.log(abs(z))
return v
@defun
def e1(ctx, z):
try:
return ctx._e1(z)
except NotImplementedError:
return ctx.expint(1, z)
@defun
def ci(ctx, z):
try:
return ctx._ci(z)
except NotImplementedError:
return ctx._ci_generic(z)
@defun_wrapped
def _ci_generic(ctx, z):
if ctx.isinf(z):
if z == ctx.inf: return ctx.zero
if z == ctx.ninf: return ctx.pi*1j
jz = ctx.fmul(ctx.j,z,exact=True)
njz = ctx.fneg(jz,exact=True)
v = 0.5*(ctx.ei(jz) + ctx.ei(njz))
zreal = ctx._re(z)
zimag = ctx._im(z)
if zreal == 0:
if zimag > 0: v += ctx.pi*0.5j
if zimag < 0: v -= ctx.pi*0.5j
if zreal < 0:
if zimag >= 0: v += ctx.pi*1j
if zimag < 0: v -= ctx.pi*1j
if ctx._is_real_type(z) and zreal > 0:
v = ctx._re(v)
return v
@defun
def si(ctx, z):
try:
return ctx._si(z)
except NotImplementedError:
return ctx._si_generic(z)
@defun_wrapped
def _si_generic(ctx, z):
if ctx.isinf(z):
if z == ctx.inf: return 0.5*ctx.pi
if z == ctx.ninf: return -0.5*ctx.pi
# Suffers from cancellation near 0
if ctx.mag(z) >= -1:
jz = ctx.fmul(ctx.j,z,exact=True)
njz = ctx.fneg(jz,exact=True)
v = (-0.5j)*(ctx.ei(jz) - ctx.ei(njz))
zreal = ctx._re(z)
if zreal > 0:
v -= 0.5*ctx.pi
if zreal < 0:
v += 0.5*ctx.pi
if ctx._is_real_type(z):
v = ctx._re(v)
return v
else:
return z*ctx.hyp1f2((1,2),(3,2),(3,2),-0.25*z*z)
@defun_wrapped
def chi(ctx, z):
nz = ctx.fneg(z, exact=True)
v = 0.5*(ctx.ei(z) + ctx.ei(nz))
zreal = ctx._re(z)
zimag = ctx._im(z)
if zimag > 0:
v += ctx.pi*0.5j
elif zimag < 0:
v -= ctx.pi*0.5j
elif zreal < 0:
v += ctx.pi*1j
return v
@defun_wrapped
def shi(ctx, z):
# Suffers from cancellation near 0
if ctx.mag(z) >= -1:
nz = ctx.fneg(z, exact=True)
v = 0.5*(ctx.ei(z) - ctx.ei(nz))
zimag = ctx._im(z)
if zimag > 0: v -= 0.5j*ctx.pi
if zimag < 0: v += 0.5j*ctx.pi
return v
else:
return z * ctx.hyp1f2((1,2),(3,2),(3,2),0.25*z*z)
@defun_wrapped
def fresnels(ctx, z):
if z == ctx.inf:
return ctx.mpf(0.5)
if z == ctx.ninf:
return ctx.mpf(-0.5)
return ctx.pi*z**3/6*ctx.hyp1f2((3,4),(3,2),(7,4),-ctx.pi**2*z**4/16)
@defun_wrapped
def fresnelc(ctx, z):
if z == ctx.inf:
return ctx.mpf(0.5)
if z == ctx.ninf:
return ctx.mpf(-0.5)
return z*ctx.hyp1f2((1,4),(1,2),(5,4),-ctx.pi**2*z**4/16)