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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_standard_curve(fl_rfi, fl_mef, beads_model, std_crv, xscale='linear', yscale='linear', xlim=None, ylim=(1.,1e8)):
 """ Plot a standard curve with fluorescence of calibration beads. Parameters fl_rfi : array_like Fluorescence of the calibration beads' subpopulations, in RFI units. fl_mef : array_like Fluorescence of the calibration beads' subpopulations, in MEF units. beads_model : function Fluorescence model of the calibration beads. std_crv : function The standard curve, mapping relative fluorescence (RFI) units to MEF units. Other Parameters xscale : str, optional Scale of the x axis, either ``linear`` or ``log``. yscale : str, optional Scale of the y axis, either ``linear`` or ``log``. xlim : tuple, optional Limits for the x axis. ylim : tuple, optional Limits for the y axis. """

    # Plot fluorescence of beads populations
    plt.plot(fl_rfi,
             fl_mef,
             'o',
             label='Beads',
             color=standard_curve_colors[0])

    # Generate points in x axis to plot beads model and standard curve.
    if xlim is None:
        xlim = plt.xlim()
    if xscale=='linear':
        xdata = np.linspace(xlim[0], xlim[1], 200)
    elif xscale=='log':
        xdata = np.logspace(np.log10(xlim[0]), np.log10(xlim[1]), 200)

    # Plot beads model and standard curve
    plt.plot(xdata,
             beads_model(xdata),
             label='Beads model',
             color=standard_curve_colors[1])
    plt.plot(xdata,
             std_crv(xdata),
             label='Standard curve',
             color=standard_curve_colors[2])

    plt.xscale(xscale)
    plt.yscale(yscale)
    plt.xlim(xlim)
    plt.ylim(ylim)
    plt.grid(True)
    plt.legend(loc = 'best')