How to use the mpld3.fig_to_html function in mpld3

# log-transform y
    df['y'] = np.log(df['y'])

    model = Prophet(weekly_seasonality=True, yearly_seasonality=True)
    model.fit(df)

    periods = PERIODS if not render else GRAPH_PERIODS

    future_data = model.make_future_dataframe(periods=periods, freq='d')
    forecast_data = model.predict(future_data)

    if render:
        matplotlib.pyplot.gcf()
        fig = model.plot(forecast_data, xlabel='Date', ylabel='log($)')
        return mpld3.fig_to_html(fig)

    forecast_data_orig = forecast_data  # make sure we save the original forecast data
    forecast_data_orig['yhat'] = np.exp(forecast_data_orig['yhat'])
    forecast_data_orig['yhat_lower'] = np.exp(forecast_data_orig['yhat_lower'])
    forecast_data_orig['yhat_upper'] = np.exp(forecast_data_orig['yhat_upper'])

    df['y_log'] = df['y']  #copy the log-transformed data to another column
    df['y'] = df['y_orig']  #copy the original data to 'y'

    # print(forecast_data_orig)
    d = forecast_data_orig['yhat'].to_dict()
    predictions = []

    for i, k in enumerate(list(d.keys())[-PERIODS:]):
        w = maya.when(f'{i+1} days from now')
        predictions.append({

fig = pylab.figure()
    for ifo in ifos:
        trigs = columns_from_file_list(file_list,
                                       ['snr', 'end_time'],
                                       ifo, start, end)
        print(trigs)
        pylab.scatter(trigs['end_time'], trigs['snr'], label=ifo,
                      color=ifo_color[ifo])

        fmt = '.12g'
        mpld3.plugins.connect(fig, mpld3.plugins.MousePosition(fmt=fmt))
    pylab.legend()
    pylab.xlabel('Time (s)')
    pylab.ylabel('SNR')
    pylab.grid()
    return mpld3.fig_to_html(fig)

mpld3.plugins.connect(fig, tooltip, TopToolbar())

        # set tick marks as blank
        ax.axes.get_xaxis().set_ticks([])
        ax.axes.get_yaxis().set_ticks([])

        # set axis as blank
        ax.axes.get_xaxis().set_visible(False)
        ax.axes.get_yaxis().set_visible(False)

    ax.legend(numpoints=1)  # show legend with only one dot

    mpld3.display()  # show the plot

    # uncomment the below to export to html
    html = mpld3.fig_to_html(fig)
    name = 'name.%s.html' % ('en' if english else 'es')
    mpld3.save_html(fig, name)

def money_scatter_plot(data_df):
    x = data_df['Current Equip. Value']
    y = data_df['Round Kills']

    fig = plt.figure()
    plt.scatter(x, y)
    plt.xlabel('Equipment Value ($)')
    plt.ylabel('# of Kills In Round')
    plt.yticks([0, 1, 2, 3, 4, 5])
    plt.suptitle('Kills/Round vs. Equipment Value')
    return mpld3.fig_to_html(fig, no_extras=True)

voffset=10, hoffset=10)#, css=self.css)

        mpld3.plugins.connect(fig, tooltip)

        if scatter_inc:
            tooltip = mpld3.plugins.PointHTMLTooltip(scatter_inc, np.array(labels)[inc_indx].tolist(),
                                                     voffset=10, hoffset=10)#, css=self.css)

        mpld3.plugins.connect(fig, tooltip)

        if self.output_dir:
            self.logger.debug("Save to %s", self.output_dir)
            with open(self.output_dir, "w") as fp:
                mpld3.save_html(fig, fp)

        html = mpld3.fig_to_html(fig)
        plt.close(fig)
        return html

def fig_to_html(fig):
    return mpld3.fig_to_html(fig)

self.x[i] = []
                self.y[i] = []

        if self.xlim_pipe is not None and output is None:
            import matplotlib.animation
            self.ani = matplotlib.animation.FuncAnimation(self.fig, self.xlim_change_check,
                                                          frames=10, interval=20000,
                                                          repeat=True, blit=False)
            threading.Timer(0.1, self.xlim_timer).start()

        if output is None:
            pylab.draw()
            pylab.show(block=block)
        elif output.endswith(".html"):
            import mpld3
            html = mpld3.fig_to_html(self.fig)
            f_out = open(output, 'w')
            f_out.write(html)
            f_out.close()
        else:
            pylab.savefig(output, bbox_inches='tight', dpi=200)

stat2 = f['foreground/stat2']
    time1 = f['foreground/time1']
    time2 = f['foreground/time2']
    ifo1 = f.attrs['detector_1']
    ifo2 = f.attrs['detector_2']

    pylab.scatter(time1, stat1, label=ifo1, color=ifo_color[ifo1])
    pylab.scatter(time2, stat2, label=ifo2, color=ifo_color[ifo2])

    fmt = '.12g'
    mpld3.plugins.connect(fig, mpld3.plugins.MousePosition(fmt=fmt))
    pylab.legend()
    pylab.xlabel('Time (s)')
    pylab.ylabel('NewSNR')
    pylab.grid()
    return mpld3.fig_to_html(fig)