def _eval_evalf(self, prec):
from mpmath import mp, workprec
from sympy import Expr
a = self.args[0]._to_mpmath(prec)
z = self.args[1]._to_mpmath(prec)
with workprec(prec):
res = mp.gammainc(a, z, mp.inf)
return Expr._from_mpmath(res, prec)
def _eval_evalf(self, prec):
from mpmath import mp, workprec
from ... import Expr
a = self.args[0]._to_mpmath(prec)
z = self.args[1]._to_mpmath(prec)
with workprec(prec):
res = mp.gammainc(a, z, mp.inf)
return Expr._from_mpmath(res, prec)
def _eval_evalf(self, prec):
if all(x.is_number for x in self.args):
a = self.args[0]._to_mpmath(prec)
z = self.args[1]._to_mpmath(prec)
with workprec(prec):
res = mp.gammainc(a, z, mp.inf)
return Expr._from_mpmath(res, prec)
return self
def _eval_evalf(self, prec):
from mpmath import mp, workprec
from sympy import Expr
if all(x.is_number for x in self.args):
a = self.args[0]._to_mpmath(prec)
z = self.args[1]._to_mpmath(prec)
with workprec(prec):
res = mp.gammainc(a, 0, z)
return Expr._from_mpmath(res, prec)
else:
return self
def _eval_evalf(self, prec):
from mpmath import mp, workprec
from sympy import Expr
if all(x.is_number for x in self.args):
a = self.args[0]._to_mpmath(prec)
z = self.args[1]._to_mpmath(prec)
with workprec(prec):
res = mp.gammainc(a, 0, z)
return Expr._from_mpmath(res, prec)
else:
return self
def BoysValue(n, x):
F = []
if x == mp.mpf("0"):
for i in range(0, n+1):
F.append(mp.mpf(1.0)/(mp.mpf(2.0*i+1)))
else:
for i in range(0, n+1):
N = i+mp.mpf("0.5")
F.append(mp.gammainc(N, 0, x) * 1.0/(2.0 * mp.power(x, N)))
return F
def FixedResGlobal(nsigma):
n_levels = len(nsigma)
q_perlevel = np.empty(n_levels, dtype=object)
for l, lev in enumerate(nsigma):
q_total = 0
nQs = len(lev)
for j, sig in enumerate(lev):
pval = mp.erfc(abs(sig)/mp.sqrt(2))
q = -2*mp.log(pval)
q_total += q
q_perlevel[l] = [q_total, nQs]
nsigma_fixedres = np.zeros(n_levels)
for i, entry in enumerate(q_perlevel):
qT = entry[0]
nQ = entry[1]
Dchi2 = mp.gammainc(nQ, 0, 0.5*qT)/mp.gamma(nQ)
nsigma_ell = mp.sqrt(2)*mp.erfinv(Dchi2)
nsigma_fixedres[i] = nsigma_ell
return nsigma_fixedres
def _eval_evalf(self, prec):
a = self.args[0]._to_mpmath(prec)
z = self.args[1]._to_mpmath(prec)
with workprec(prec):
res = mp.gammainc(a, z, mp.inf)
return Expr._from_mpmath(res, prec)
ocl_function=make_ocl("return sas_gamma(q);", "sas_gamma",
["lib/sas_gamma.c"]),
limits=(-3.1, 10),
)
add_function(
name="gammaln(x)",
mp_function=mp.loggamma,
np_function=scipy.special.gammaln,
ocl_function=make_ocl("return sas_gammaln(q);", "sas_gammaln",
["lib/sas_gammainc.c"]),
#ocl_function=make_ocl("return lgamma(q);", "sas_gammaln"),
)
add_function(
# Note: "a" is given as A=... on the command line via parse_extra_pars
name="gammainc(x)",
mp_function=lambda x, a=A: mp.gammainc(a, a=0, b=x) / mp.gamma(a),
np_function=lambda x, a=A: scipy.special.gammainc(a, x),
ocl_function=make_ocl("return sas_gammainc(%.15g,q);" % A, "sas_gammainc",
["lib/sas_gammainc.c"]),
)
add_function(
# Note: "a" is given as A=... on the command line via parse_extra_pars
name="gammaincc(x)",
mp_function=lambda x, a=A: mp.gammainc(a, a=x, b=mp.inf) / mp.gamma(a),
np_function=lambda x, a=A: scipy.special.gammaincc(a, x),
ocl_function=make_ocl("return sas_gammaincc(%.15g,q);" % A,
"sas_gammaincc", ["lib/sas_gammainc.c"]),
)
add_function(
name="erf(x)",
mp_function=mp.erf,
def _eval_evalf(self, prec):
a = self.args[0]._to_mpmath(prec)
z = self.args[1]._to_mpmath(prec)
with workprec(prec):
res = mp.gammainc(a, z, mp.inf)
return Expr._from_mpmath(res, prec)
