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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 generated(self, band, t, err=None, corrected=True):
 """Return generated magnitudes in the specified band Parameters band : str desired bandpass: should be one of ['u', 'g', 'r', 'i', 'z'] t : array_like array of times (in days) err : float or array_like gaussian error in observations corrected : bool (optional) If true, correct for extinction Returns ------- mag : ndarray magnitudes at the specified times under the generated model. """

        t = np.asarray(t)
        num = self.meta[band + 'T']
        mu = self.meta[band + '0']
        amp = self.meta[band + 'A']
        t0 = self.meta[band + 'E']

        # if there are nans or infinities, mask them
        bad_vals = np.isnan(t) | np.isinf(t)
        t[bad_vals] = t0

        if corrected:
            ext = 0
        else:
            ext = self.obsmeta['rExt'] * self.ext_correction[band]

        func = self._template_func(num, band, mu + ext, amp)
        mag = func(((t - t0) / self.period) % 1)

        mag[bad_vals] = np.nan

        if err is not None:
            mag += self.rng.normal(0, err, t.shape)

        return mag