<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def spectra(self, itaper=None, nwin=None, convention='power', unit='per_l', base=10.):
 """ Return the spectra of one or more localization windows. Usage ----- spectra = x.spectra([itaper, nwin, convention, unit, base]) Returns ------- spectra : ndarray, shape (lwin+1, nwin) A matrix with each column containing the spectrum of a localization window, and where the windows are arranged with increasing concentration factors. If itaper is set, only a single vector is returned, whereas if nwin is set, the first nwin spectra are returned. Parameters itaper : int, optional, default = None The taper number of the output spectrum, where itaper=0 corresponds to the best concentrated taper. nwin : int, optional, default = 1 The number of best concentrated localization window power spectra to return. convention : str, optional, default = 'power' The type of spectrum to return: 'power' for power spectrum, 'energy' for energy spectrum, and 'l2norm' for the l2 norm spectrum. unit : str, optional, default = 'per_l' If 'per_l', return the total contribution to the spectrum for each spherical harmonic degree l. If 'per_lm', return the average contribution to the spectrum for each coefficient at spherical harmonic degree l. If 'per_dlogl', return the spectrum per log interval dlog_a(l). base : float, optional, default = 10. The logarithm base when calculating the 'per_dlogl' spectrum. Description This function returns either the power spectrum, energy spectrum, or l2-norm spectrum of one or more of the localization windows. Total power is defined as the integral of the function squared over all space, divided by the area the function spans. If the mean of the function is zero, this is equivalent to the variance of the function. The total energy is the integral of the function squared over all space and is 4pi times the total power. The l2-norm is the sum of the magnitude of the coefficients squared. The output spectrum can be expresed using one of three units. 'per_l' returns the contribution to the total spectrum from all angular orders at degree l. 'per_lm' returns the average contribution to the total spectrum from a single coefficient at degree l. The 'per_lm' spectrum is equal to the 'per_l' spectrum divided by (2l+1). 'per_dlogl' returns the contribution to the total spectrum from all angular orders over an infinitessimal logarithmic degree band. The contrubution in the band dlog_a(l) is spectrum(l, 'per_dlogl')*dlog_a(l), where a is the base, and where spectrum(l, 'per_dlogl) is equal to spectrum(l, 'per_l')*l*log(a). """

        if itaper is None:
            if nwin is None:
                nwin = self.nwin
            spectra = _np.zeros((self.lwin+1, nwin))

            for iwin in range(nwin):
                coeffs = self.to_array(iwin)
                spectra[:, iwin] = _spectrum(coeffs, normalization='4pi',
                                             convention=convention, unit=unit,
                                             base=base)
        else:
            coeffs = self.to_array(itaper)
            spectra = _spectrum(coeffs, normalization='4pi',
                                convention=convention, unit=unit, base=base)

        return spectra