def rstable_sym(self, alpha, location, scale, \
xmin=float('-inf'), xmax=float('inf'), \
pmin=0.0, pmax=1.0):
"""
The SYMMETRICAL stable distribution where alpha is the tail exponent.
For numerical reasons alpha is restricted to [0.25, 0.9] and
[1.125, 1.9] - but alpha = 1.0 (the Cauchy) and alpha = 2.0 (scaled
normal) are also allowed!
Numerics are somewhat crude but the fractional error is mostly < 0.001 -
sometimes much less - and the absolute error is almost always < 0.001 -
sometimes much less...
NB This generator is slow - particularly for small alpha !!!!!
"""
self._checkminmax(xmin, xmax, pmin, pmax, 'rstable_sym')
pmn = pmin
pmx = pmax
if xmin > float('-inf'):\
pmn = max(pmin, cstable_sym(alpha, location, scale, xmin))
if xmax < float('inf'): \
pmx = min(pmax, cstable_sym(alpha, location, scale, xmax))
p = pmn + (pmx-pmn)*self.runif01()
x = istable_sym(p, alpha, location, scale)
return x
def _fifi2fid(x):
cdf = cstable_sym(alpha, location, scale, x)
pdf = dstable_sym(alpha, location, scale, x)
fi = cdf - prob
if pdf <= 0.0:
if fi == 0.0: fi2fid = 1.0
else: fi2fid = MAXFLOAT
else:
fi2fid = fi/pdf
return fi, fi2fid