def _ve_gauss_(s, accept=lambda a: True, nmax=1000):
""" Get the gaussian random number
>>> v = ... ## the number with error
## get 100 random numbers
>>> for i in range ( 0, 100 ) : print v.gauss()
## get only non-negative numbers
>>> for j in range ( 0, 100 ) : print v.gauss( lambda s : s > 0 )
"""
#
if 0 >= s.cov2() or iszero(s.cov2()): return s.value() ## return
#
v = s.value()
e = s.error()
#
for i in xrange(nmax):
r = _gauss(v, e)
if accept(r): return r
logger.warning("Can'n generate proper random number %s" % s)
return v
def zMass(mZ=91.188, wZ=2.495):
"""Return a gaussian distribution. Default has a mean of 91.188 and a
width of 2.495."""
return _gauss(mZ, wZ * (2 * _sqrt(2 * _log(2))))