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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 plot_samples( ax, sampler, modelidx=0, sed=True, n_samples=100, e_unit=u.eV, e_range=None, e_npoints=100, threads=None, label=None, last_step=False, ):
 """Plot a number of samples from the sampler chain. Parameters ax : `matplotlib.Axes` Axes to plot on. sampler : `emcee.EnsembleSampler` Sampler modelidx : int, optional Model index. Default is 0 sed : bool, optional Whether to plot SED or differential spectrum. If `None`, the units of the observed spectrum will be used. n_samples : int, optional Number of samples to plot. Default is 100. e_unit : :class:`~astropy.units.Unit` or str parseable to unit Unit in which to plot energy axis. e_range : list of `~astropy.units.Quantity`, length 2, optional Limits in energy for the computation of the model samples and ML model. Note that setting this parameter will mean that the samples for the model are recomputed and depending on the model speed might be quite slow. e_npoints : int, optional How many points to compute for the model samples and ML model if `e_range` is set. threads : int, optional How many parallel processing threads to use when computing the samples. Defaults to the number of available cores. last_step : bool, optional Whether to only use the positions in the final step of the run (True, default) or the whole chain (False). """


    modelx, model = _read_or_calc_samples(
        sampler,
        modelidx,
        last_step=last_step,
        e_range=e_range,
        e_npoints=e_npoints,
        threads=threads,
    )
    # pick first model sample for units
    f_unit, sedf = sed_conversion(modelx, model[0].unit, sed)

    sample_alpha = min(5.0 / n_samples, 0.5)
    for my in model[np.random.randint(len(model), size=n_samples)]:
        ax.loglog(
            modelx.to(e_unit).value,
            (my * sedf).to(f_unit).value,
            color=(0.1,) * 3,
            alpha=sample_alpha,
            lw=1.0,
        )

    _plot_MLmodel(ax, sampler, modelidx, e_range, e_npoints, e_unit, sed)

    if label is not None:
        ax.set_ylabel(
            "{0} [{1}]".format(label, f_unit.to_string("latex_inline"))
        )