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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 from_zeros(self, lmax, gm, r0, omega=None, errors=False, normalization='4pi', csphase=1):
 """ Initialize the class with spherical harmonic coefficients set to zero from degree 1 to lmax, and set the degree 0 term to 1. Usage ----- x = SHGravCoeffs.from_zeros(lmax, gm, r0, [omega, errors, normalization, csphase]) Returns ------- x : SHGravCoeffs class instance. Parameters lmax : int The maximum spherical harmonic degree l of the coefficients. gm : float The gravitational constant times the mass that is associated with the gravitational potential coefficients. r0 : float The reference radius of the spherical harmonic coefficients. omega : float, optional, default = None The angular rotation rate of the body. errors : bool, optional, default = False If True, initialize the attribute errors with zeros. normalization : str, optional, default = '4pi' '4pi', 'ortho', 'schmidt', or 'unnorm' for geodesy 4pi normalized, orthonormalized, Schmidt semi-normalized, or unnormalized coefficients, respectively. csphase : int, optional, default = 1 Condon-Shortley phase convention: 1 to exclude the phase factor, or -1 to include it. """

        if normalization.lower() not in ('4pi', 'ortho', 'schmidt', 'unnorm'):
            raise ValueError(
                "The normalization must be '4pi', 'ortho', 'schmidt', "
                "or 'unnorm'. Input value was {:s}."
                .format(repr(normalization))
                )

        if csphase != 1 and csphase != -1:
            raise ValueError(
                "csphase must be either 1 or -1. Input value was {:s}."
                .format(repr(csphase))
                )

        if normalization.lower() == 'unnorm' and lmax > 85:
            _warnings.warn("Calculations using unnormalized coefficients "
                           "are stable only for degrees less than or equal "
                           "to 85. lmax for the coefficients will be set to "
                           "85. Input value was {:d}.".format(lmax),
                           category=RuntimeWarning)
            lmax = 85

        coeffs = _np.zeros((2, lmax + 1, lmax + 1))
        coeffs[0, 0, 0] = 1.0

        if errors is False:
            clm = SHGravRealCoeffs(coeffs, gm=gm, r0=r0, omega=omega,
                                   normalization=normalization.lower(),
                                   csphase=csphase)
        else:
            clm = SHGravRealCoeffs(coeffs, gm=gm, r0=r0, omega=omega,
                                   errors=_np.zeros((2, lmax + 1, lmax + 1)),
                                   normalization=normalization.lower(),
                                   csphase=csphase)
        return clm