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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 _pseudoinverse(self, A, tol=1.0e-10):
 """Compute the Moore-Penrose pseudoinverse, wraps np.linalg.pinv REQUIRED ARGUMENTS A (np KxK matrix) - the square matrix whose pseudoinverse is to be computed RETURN VALUES Ainv (np KxK matrix) - the pseudoinverse OPTIONAL VALUES tol - the tolerance (relative to largest magnitude singlular value) below which singular values are to not be include in forming pseudoinverse (default: 1.0e-10) NOTES In previous versions of pymbar / Numpy, we wrote our own pseudoinverse because of a bug in Numpy. """


        return np.linalg.pinv(A, rcond=tol)