def LogLikelihood(self, data):
m = len(data)<EOL>if self.n < m:<EOL><INDENT>return float('<STR_LIT>')<EOL><DEDENT>x = self.Random()<EOL>y = numpy.log(x[:m]) * data<EOL>return y.sum()<EOL>
Computes the log likelihood of the data.

        Selects a random vector of probabilities from this distribution.

        Returns: float log probability