How to use the mpld3.fig_to_dict function in mpld3

[r[0] for r in rnd_draws], 50,
            normed=1, facecolor='green', alpha=0.75
        )
        self.ax2.cla()
        self.ax2.set_xlabel('r2')
        self.ax2.set_ylabel('Normalized Distribtuion')
        self.ax2.set_xlim(0, 1)
        self.ax2.set_ylim(0, 1.5)
        self.ax2.grid(True)
        self.ax2.hist(
            [r[1] for r in rnd_draws], 50,
            normed=1, facecolor='blue', alpha=0.75
        )

        # send new matplotlib plots to frontend
        self.emit('mpld3canvas', mpld3.fig_to_dict(self.fig))

return_dict['y_min'] = y_min
    return_dict['y_max'] = y_max

    fig, ax = plt.subplots(subplot_kw=dict(axisbg='#EEEEEE'))
    for alg_dict in list_of_alg_dicts:
        ax.plot(alg_dict['x'],alg_dict['y'],label=alg_dict['legend_label'])
    ax.set_xlabel('API Call')
    ax.set_ylabel('Duration (s)')
    ax.set_xlim([x_min,x_max])
    ax.set_ylim([y_min,y_max])
    ax.grid(color='white', linestyle='solid')
    ax.set_title(task, size=14)
    legend = ax.legend(loc=2,ncol=3,mode="expand")
    for label in legend.get_texts():
      label.set_fontsize('small')
    plot_dict = mpld3.fig_to_dict(fig)
    plt.close()
    return plot_dict

def Cat_ViolinPlot(data, x, y=None, hue=None):
    sns.set_style("whitegrid")
    g = sns.violinplot(x, y, data, hue=hue)
    d = mpld3.fig_to_dict(g.figure)
    return d

import matplotlib.pyplot as plt
        import mpld3
        fig, ax = plt.subplots(subplot_kw=dict(axisbg='#EEEEEE'))
        for alg_dict in list_of_alg_dicts:
            ax.plot(alg_dict['x'],alg_dict['y'],label=alg_dict['legend_label'])
        ax.set_xlabel('Number of answered queries')
        ax.set_ylabel('Error on hold-out set')
        ax.set_xlim([x_min,x_max])
        ax.set_ylim([y_min,y_max])
        ax.grid(color='white', linestyle='solid')
        ax.set_title('Test Error', size=14)
        legend = ax.legend(loc=2,ncol=3,mode="expand")
        for label in legend.get_texts():
          label.set_fontsize('small')
        plot_dict = mpld3.fig_to_dict(fig)
        plt.close()

        return plot_dict

import matplotlib.pyplot as plt
    import mpld3
    fig, ax = plt.subplots(subplot_kw=dict(axisbg='#FFFFFF'))
    ax.hist(numerical_timestamps,int(1+4*numpy.sqrt(len(numerical_timestamps))),alpha=0.5,color='black')
    ax.set_axis_off()
    # ax.set_xlabel('API Call')
    # ax.set_ylabel('Duration (s)')
    #ax.set_xlim([x_min,x_max])
    #ax.set_ylim([y_min,y_max])
    #ax.grid(color='white', linestyle='solid')
    # ax.set_title(task, size=14)
    # labels = ['point {0}'.format(i + 1) for i in range(N)]
    # tooltip = mpld3.plugins.PointLabelTooltip(scatter, labels=labels)
    # mpld3.plugins.connect(fig, tooltip)
    plot_dict = mpld3.fig_to_dict(fig)

    
    return plot_dict

def savehtml(self, filename):
        import mpld3
#        mpld3.save_html(self.figure,filename)
#        mpld3.save_json(self.figure, filename)
        mpld3.fig_to_dict(self.figure)

def Reg_RegPlot(data, x, y):
    sns.set_style("whitegrid")
    g = sns.regplot(x, y, data)
    d = mpld3.fig_to_dict(g.figure)
    return d

def Cat_LVPlot(data, x, y=None, hue=None):
    sns.set_style("whitegrid")
    g = sns.lvplot(x, y, data, hue=hue)
    d = mpld3.fig_to_dict(g.figure)
    return d

def Axis_LMPlot(data, x, y=None, hue=None):
    sns.set(color_codes=True)
    ax = sns.lmplot(x=x, y=y, hue=hue, data=data)
    d = mpld3.fig_to_dict(ax.fig)

    return d

fig, ax = plt.subplots(subplot_kw=dict(axisbg='#EEEEEE'))
    for alg_dict in list_of_alg_dicts:
        ax.plot(alg_dict['x'],alg_dict['y'],label=alg_dict['legend_label'])
    ax.set_xlabel('API Call')
    ax.set_ylabel('Duration (s)')
    ax.set_xlim([x_min,x_max])
    ax.set_ylim([y_min,y_max])
    ax.grid(color='white', linestyle='solid')
    ax.set_title(task, size=14)
    legend = ax.legend(loc=2,ncol=3,mode="expand")
    for label in legend.get_texts():
      label.set_fontsize('small')
    # labels = ['point {0}'.format(i + 1) for i in range(N)]
    # tooltip = mpld3.plugins.PointLabelTooltip(scatter, labels=labels)
    # mpld3.plugins.connect(fig, tooltip)
    plot_dict = mpld3.fig_to_dict(fig)


    return plot_dict