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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def LogLikelihood(self, data):
 """Computes the log likelihood of the data. Selects a random vector of probabilities from this distribution. Returns: float log probability """

        m = len(data)
        if self.n < m:
            return float('-inf')

        x = self.Random()
        y = numpy.log(x[:m]) * data
        return y.sum()