def _fifi2fid(x):
x = kept_within(0.0, x)
cdf = cfoldednormal(muunfold, sigmaunfold, x)
pdf = dfoldednormal(muunfold, sigmaunfold, 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
def rfoldednormal(self, muunfold, sigmaunfold, xmax=float('inf'), pmax=1.0):
"""
The distribution of a random variable that is the absolute value
of a variate drawn from the normal distribution (i. e. the distribution
of a variate that is the absolute value of a normal variate, the latter
having muunfold as its mean and sigmaunfold as its standard deviation).
sigmaunfold >= 0.0
"""
assert xmax >= 0.0, \
"xmax must be a non-negative float in rfoldednormal!"
self._checkpmax(pmax, 'rfoldednormal')
pmx = pmax
if xmax < float('inf'): \
pmx = min(pmax, cfoldednormal(muunfold, sigmaunfold, xmax))
p = pmx * self.runif01()
x = ifoldednormal(p, muunfold, sigmaunfold)
return x
