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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 lstsq(cls, a, b):
 """Return the least-squares solution to a linear matrix equation. :param Matrix a: Design matrix with the values of the independent variables. :param Matrix b: Matrix with the "dependent variable" values. b can only have one column. :raise: Raises an :py:exc:`ValueError`, if - the number of rows of a and b does not match. - b has more than one column. :note: The algorithm solves the following equations. beta = a^+ b. """

        # Check if the size of the input matrices matches
        if a.get_height() != b.get_height():
            raise ValueError("Size of input matrices does not match")
        if b.get_width() != 1:
            raise ValueError("Matrix with dependent variable has more than 1 column")
        aPseudo = a.pseudoinverse()
        # The following code could be used if c is regular.
        # aTrans  = a.transform()
        # c       = aTrans * a
        # invers() raises an ValueError, if c is not invertible
        # cInvers = c.invers()
        # beta = cInvers * aTrans * b
        beta = aPseudo * b
        return beta