def Exp(self, m=None):
        """Exponentiates the probabilities.

        m: how much to shift the ps before exponentiating

        If m is None, normalizes so that the largest prob is 1.
        """
        if not self.log:
            raise ValueError("Pmf/Hist not under a log transform")
        self.log = False

        if m is None:
            m = self.MaxLike()

        for x, p in self.d.iteritems():
            self.Set(x, math.exp(p - m))
def Exp ( self , m = None ) : if not self . log : raise ValueError ( "Pmf/Hist not under a log transform" ) self . log = False if m is None : m = self . MaxLike ( ) for x , p in self . d . iteritems ( ) : self . Set ( x , math . exp ( p - m ) )
Exponentiates the probabilities.

        m: how much to shift the ps before exponentiating

        If m is None, normalizes so that the largest prob is 1.