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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 _genA(self):
 """ Generate the matrix A in the Bartlett decomposition A is a lower triangular matrix, with A(i, j) ~ sqrt of Chisq(df - i + 1) when i == j ~ Normal() when i > j """

        p, df = self._p, self.df
        A = np.zeros((p, p))

        for i in range(p):
            A[i, i] = sqrt(st.chi2.rvs(df - i))

        for j in range(p-1):
            for i in range(j+1, p):
                A[i, j] = np.random.randn()

        return A